p1.pdf
•
0 likes•3 views
This document is about artificial intelligence and discusses key concepts such as defining AI as making machines seem intelligent like humans, the goal of mimicking the human brain, and how AI is expected to behave intelligently. It notes that AI will take on the role of intelligent workers by automating tasks, but that human experts will still be needed to build and maintain AI systems and work on creative aspects of jobs.
Report
Share
Report
Share
Download to read offline
Recommended
Artificial intelligence
The document provides an introduction to artificial intelligence (AI), including definitions of AI, descriptions of the eras of AI development, types of AI approaches, and applications of AI. It discusses factors that have influenced recent advancement in AI and identifies areas of AI research focus. The summary is:
The document introduces artificial intelligence (AI), defining it as human-made thinking power. It describes the history and eras of AI development, different types and approaches of AI including weak AI, strong AI, and super AI. Furthermore, it discusses applications of AI and factors influencing recent advancement, and identifies areas of ongoing AI research focus.
Chapter 3 - EMTE.pptx
The document provides an introduction to artificial intelligence, including what AI is, its history and development over different eras. It discusses the types and approaches of AI, including reactive machines, limited memory systems, theory of mind and self-awareness. It also outlines how AI systems map to human thinking processes and how factors like advances in computing, big data, cloud computing and data science have influenced AI's development. Finally, it gives examples of real-world AI applications in various fields such as transportation, healthcare, home services and public safety.
Chapter Three, four, five and six.ppt ITEtx
Artificial intelligence (AI) can be summarized as follows:
(1) AI refers to creating intelligent machines that can think and act like humans. It involves machines acquiring knowledge and applying it through experience to solve complex problems.
(2) The key components of human intelligence - learning, reasoning, problem-solving, perception, and linguistic ability - form the basis for developing AI systems.
(3) As data and computing power have increased, AI has advanced from narrow applications to more general problem-solving abilities through techniques like machine learning, neural networks, and deep learning.
Artificial intelligence DG.pptx
This document discusses artificial intelligence (AI) and was presented by Group 07 for their course on Differential Geometry-II. It defines AI as making machines that can think and act like humans. The goals of AI include replicating human intelligence and solving knowledge-intensive tasks. AI requires understanding of computer science, mathematics, psychology and other fields. While AI offers advantages like accuracy, speed and reliability, it also has disadvantages such as high costs, inability to think creatively, and lack of emotions.
Ai
This document discusses different types and approaches to artificial intelligence:
1. The Turing Test approach aims to create AI that can converse with humans in natural language without being distinguished from a human. This requires capabilities in natural language processing, knowledge representation, automated reasoning, and machine learning.
2. The cognitive modeling approach seeks to understand human thought through introspection, psychological experiments observing human behavior, and brain imaging to then model human thinking in AI.
3. The "laws of thought" approach uses logic and probability to model rational thought, moving from perception to understanding how the world works to predicting the future.
4. The rational agent approach creates agents that can autonomously perceive their environment, act
Artificial Intelligence Lecture-3
Artificial Intelligence, Areas of Artificial Intelligence, Examples of Artificial Intelligence, Applications of Artificial Intelligence, Data Mining, Robot etc.
Artificial intelligence nanni
This document provides an overview of the history and applications of artificial intelligence (AI). It discusses:
- The origins of AI beginning in the 1940s with the development of electronic computers.
- Key early developments including the Dartmouth Conference in 1956 and the creation of the LISP programming language.
- Military funding of AI research during the Cold War and development of early expert systems.
- Current applications of AI across various fields such as military, science, industry, business, consumer products, and entertainment.
- Ongoing debates around the future capabilities of AI and important ethical considerations surrounding advanced AI technologies.
Artificial intelligence-full -report.doc
This document provides an introduction and overview of artificial intelligence (AI). It discusses the history of AI, including early programs in the 1950s-1960s and advances such as neural networks and deep learning. It defines AI and describes its goals such as reasoning, knowledge representation, planning, natural language processing, perception, and social intelligence. The document outlines two main categories of AI: conventional AI which uses symbolic and statistical methods, and computational intelligence which uses machine learning techniques like neural networks. It gives examples of applications such as pattern recognition, robotics, and game playing. Finally, it discusses related fields where AI is used such as automation, cybernetics, and intelligent control systems.
Recommended
Artificial intelligence
The document provides an introduction to artificial intelligence (AI), including definitions of AI, descriptions of the eras of AI development, types of AI approaches, and applications of AI. It discusses factors that have influenced recent advancement in AI and identifies areas of AI research focus. The summary is:
The document introduces artificial intelligence (AI), defining it as human-made thinking power. It describes the history and eras of AI development, different types and approaches of AI including weak AI, strong AI, and super AI. Furthermore, it discusses applications of AI and factors influencing recent advancement, and identifies areas of ongoing AI research focus.
Chapter 3 - EMTE.pptx
The document provides an introduction to artificial intelligence, including what AI is, its history and development over different eras. It discusses the types and approaches of AI, including reactive machines, limited memory systems, theory of mind and self-awareness. It also outlines how AI systems map to human thinking processes and how factors like advances in computing, big data, cloud computing and data science have influenced AI's development. Finally, it gives examples of real-world AI applications in various fields such as transportation, healthcare, home services and public safety.
Chapter Three, four, five and six.ppt ITEtx
Artificial intelligence (AI) can be summarized as follows:
(1) AI refers to creating intelligent machines that can think and act like humans. It involves machines acquiring knowledge and applying it through experience to solve complex problems.
(2) The key components of human intelligence - learning, reasoning, problem-solving, perception, and linguistic ability - form the basis for developing AI systems.
(3) As data and computing power have increased, AI has advanced from narrow applications to more general problem-solving abilities through techniques like machine learning, neural networks, and deep learning.
Artificial intelligence DG.pptx
This document discusses artificial intelligence (AI) and was presented by Group 07 for their course on Differential Geometry-II. It defines AI as making machines that can think and act like humans. The goals of AI include replicating human intelligence and solving knowledge-intensive tasks. AI requires understanding of computer science, mathematics, psychology and other fields. While AI offers advantages like accuracy, speed and reliability, it also has disadvantages such as high costs, inability to think creatively, and lack of emotions.
Ai
This document discusses different types and approaches to artificial intelligence:
1. The Turing Test approach aims to create AI that can converse with humans in natural language without being distinguished from a human. This requires capabilities in natural language processing, knowledge representation, automated reasoning, and machine learning.
2. The cognitive modeling approach seeks to understand human thought through introspection, psychological experiments observing human behavior, and brain imaging to then model human thinking in AI.
3. The "laws of thought" approach uses logic and probability to model rational thought, moving from perception to understanding how the world works to predicting the future.
4. The rational agent approach creates agents that can autonomously perceive their environment, act
Artificial Intelligence Lecture-3
Artificial Intelligence, Areas of Artificial Intelligence, Examples of Artificial Intelligence, Applications of Artificial Intelligence, Data Mining, Robot etc.
Artificial intelligence nanni
This document provides an overview of the history and applications of artificial intelligence (AI). It discusses:
- The origins of AI beginning in the 1940s with the development of electronic computers.
- Key early developments including the Dartmouth Conference in 1956 and the creation of the LISP programming language.
- Military funding of AI research during the Cold War and development of early expert systems.
- Current applications of AI across various fields such as military, science, industry, business, consumer products, and entertainment.
- Ongoing debates around the future capabilities of AI and important ethical considerations surrounding advanced AI technologies.
Artificial intelligence-full -report.doc
This document provides an introduction and overview of artificial intelligence (AI). It discusses the history of AI, including early programs in the 1950s-1960s and advances such as neural networks and deep learning. It defines AI and describes its goals such as reasoning, knowledge representation, planning, natural language processing, perception, and social intelligence. The document outlines two main categories of AI: conventional AI which uses symbolic and statistical methods, and computational intelligence which uses machine learning techniques like neural networks. It gives examples of applications such as pattern recognition, robotics, and game playing. Finally, it discusses related fields where AI is used such as automation, cybernetics, and intelligent control systems.
DWX 2018 Session about Artificial Intelligence, Machine and Deep Learning
Artificial intelligence, machine learning, and deep learning provide benefits but also risks that should be addressed ethically and responsibly. AI has progressed due to exponential data growth, large unstructured datasets, improved hardware, and falling error rates. Deep learning in particular has advanced areas like computer vision, speech recognition and games. While concerns exist around a potential artificial general intelligence, AI also enables applications in healthcare, transportation, science and more. Individuals and companies are encouraged to start experimenting with and adopting machine learning.
Addis abeb university ..Artificial intelligence .pptx
The document defines artificial intelligence as the science and engineering of making intelligent machines, especially intelligent computer programs. It discusses that AI is the creation of computer programs that can learn to think and function on their own. The document then provides examples of technologies that use AI, such as machine learning, robotics, and neural networks. It describes the different types of AI as artificial narrow intelligence, artificial general intelligence, and artificial super intelligence. The document also outlines the history of AI and discusses its applications in various domains like agriculture, healthcare, business, and education.
Artificial Intelligence
This Presentation will give you an overview about Artificial Intelligence : definition, advantages , disadvantages , benefits , applications .
We hope it to be useful .
Selected topics in Computer Science
This document provides an overview of selected topics in computer science, including artificial intelligence, robotics, machine learning, and the internet of things. It will cover these topics through a series of sessions, discussing introductions and basic concepts for each. The first session introduces AI and compares it to machine learning. Subsequent sessions will cover robotics and its types, applications of machine learning, and laws of robotics. Students will work on individual or group projects related to these topics.
AI - An overwiew - presentation.pptx
This document provides an overview of artificial intelligence (AI) presented by Dr. Jeyadeepa R. It begins with defining key terms like intelligence and AI. It then lists the objectives which include defining AI, listing its domains, outlining its history, differentiating human and artificial intelligence, explaining aspects of AI, classifying types of AI, and describing the need for and pros and cons of AI. The document provides details on the history and evolution of AI, achievements in the field, differences between human and artificial intelligence, central principles, types of AI classified by functionality and capabilities, and need and applications of AI. It concludes by thanking the audience.
Artificial Intelligence Report
This document provides a case study on Google DeepMind and artificial intelligence. It discusses DeepMind's work in machine learning, deep reinforcement learning, and its creation of AlphaGo which was able to defeat professional Go players. The document also briefly outlines DeepMind's work in healthcare by collaborating with hospitals to analyze medical scans and develop algorithms to differentiate healthy and cancerous tissues. However, DeepMind's data sharing agreement with the Royal Free London NHS Foundation Trust to access patient medical records without consent was controversial.
Technologies Demystified: Artificial Intelligence
This document provides an overview of artificial intelligence (AI) including definitions of different types of AI, a brief history of AI, potential application fields and use cases, and the future outlook for AI. It defines AI as ranging from everyday applications to self-driving cars. It discusses narrow AI, general AI, and superintelligence. The document also summarizes key milestones in the development of AI from 1955 to the present and potential opportunities and challenges of AI including automation, ethics, and politics. It provides examples of Austrian AI startups and their technologies. The outlook suggests that human-level AI may be achieved by 2040 and superintelligence by 2060 with impacts on robotics, climate change, human enhancement, and autonomous
Artificial intelligence
just hvae a look, m sure u whould lyk it...............................................................................................................................................................................its all about artificial machines.....................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
Future aspects of ai by rahul abhishek
This document discusses the future of artificial intelligence. It describes how AI is currently being used in fields like robotics, gaming, and healthcare. The document outlines that in the future, AI may be able to match or surpass human-level intelligence. It also discusses potential risks of advanced AI, such as artificial intelligences that do not have human-like motivations and may pursue goals that do not align with human values. The document concludes that accurately predicting the capabilities and impacts of future AI remains challenging.
Artificial intelligence introduction
Artificial intelligence (AI) aims to build intelligent machines that can perform tasks requiring human intelligence. The goals of AI are to better understand human intelligence by modeling it in computer programs, and to create useful programs that can perform expert tasks. Many disciplines contribute to AI including computer science, psychology, philosophy, linguistics, and biology. Typical AI problems involve both mundane tasks like shopping and expert tasks like medical diagnosis. Philosophical issues in AI include what intelligence is, whether machines can truly be intelligent, and if human intelligence can be reduced to rules and calculations. This module will cover AI programming, knowledge representation, search techniques, natural language processing, machine learning, intelligent agents, and knowledge engineering.
AI 3.0: Is it Finally Time for Artificial Intelligence and Sensor Networks to...
Artificial intelligence and sensor networks may now be poised to disrupt various industries and jobs. Recent advances in algorithms, sensors, data collection, mobile technology, and robotics have increased concerns about the potential threats of artificial superintelligence ending humanity. The rapid changes in science and technology could significantly impact jobs in the coming decades as AI and automation replace many human roles.
Cognitive computing
The document discusses cognitive computing, which relies on techniques like expert systems, statistics, and mathematical models to mimic human reasoning. Cognitive computing systems can handle uncertainties and complex problems through experience and learning. The key aspects are:
- Cognitive computing represents self-learning systems that use machine learning models to mimic the human brain.
- The "brain" of cognitive systems is the neural network, which underlies deep learning.
- Cognitive computing aims to simulate human thought to solve complex problems through data analysis, pattern recognition, and natural language processing like the human brain.
Artificial intelligence
Artificial Intelligence : The discipline that attempts to build entities that do perceive, understand, predict, manipulate the world around us which is manifestly much larger than us.
Artificial Intelligence.pptx
Artificial intelligence (AI) is defined as the intelligence exhibited by machines or software. It involves the study and design of intelligent agents that can perceive their environment and take actions to maximize their success. There are four schools of thought on AI: thinking humanly, thinking rationally, acting humanly, and acting rationally. AI draws from many fields including mathematics, computer science, philosophy, linguistics, psychology, economics, and sociology. Some applications of AI include smart search algorithms, natural language processing for tasks like machine translation and summarization, knowledge bases for expert systems and medical diagnosis, and machine learning for tasks like face recognition and autonomous vehicles.
Sesi 1-1 Pengantar AI.pdf
AI is the study of intelligent agents: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Major areas of AI research include reasoning, knowledge, planning, learning, natural language processing, perception and the ability to move and manipulate objects. Weak AI is limited to a specific task, while strong AI exhibits human-level intelligence across all cognitive tasks. The foundations of AI include philosophy, mathematics, psychology and linguistics. Notable AI milestones include Deep Blue defeating Kasparov at chess in 1997 and the development of expert systems, robotics, computer vision and natural language processing. Current trends include cognitive computing, which aims to develop systems that can perceive, learn, reason and assist
AI (E Group)-1.pptx
This document discusses artificial intelligence (AI) and its applications in education. It defines AI as the ability of computers to perform tasks typically requiring human intelligence. The document then provides a brief history of AI, explains why computers are well-suited for certain tasks, and lists some key characteristics of AI like deep learning and facial recognition. It describes three main types of AI - narrow/weak AI, general/strong AI, and super AI - and four types based on functionality: reactive machines, limited memory, theory of mind, and self-awareness. Finally, it outlines several future applications of AI in education like personalized learning, intelligent tutoring systems, automated grading, and predictive analytics.
AI Foundation, Challenges and Applications.pptx
The document discusses an introduction to artificial intelligence lecture. It defines AI as the power of machines to mimic human behavior. It outlines the history, purposes, and foundations of AI, including logic, mathematics, psychology, computer science, linguistics. Examples of AI applications discussed include chatbots, self-driving cars, face recognition, and robotics. The types of AI are described as weak, strong, and super AI. The components of AI discussed are learning, reasoning, problem solving, perception, and language understanding. Challenges and issues with AI like costs, unemployment, and lack of emotions are also covered.
Artificial intelligence
Artificial intelligence (AI) is a broad field that combines computer science, psychology, and philosophy with the goal of creating machines that can think like humans. AI aims to develop intelligent agents that can perceive their environment and take actions to maximize their success. The main fields of AI include machine vision, expert systems, and creating machines that can think rationally or act like humans. The goals of AI include solving complex problems, enhancing human and computer interactions, and developing the theory and practice of building intelligent machines.
A Seminar Report on Artificial Intelligence
This is a seminar report on Artificial Intelligence. This is mainly concerned for engineering projects & reports. This is actually done for presentation purpose.
LecccccccccccccProgrammingLecture-09.pdf
The document discusses development, testing, and debugging of programs. It covers the differences between correctness testing, which detects errors by comparing actual and expected results, and debugging, which fixes errors found during testing. Broad categories of errors like syntax, runtime, and semantic errors are described. The importance of function specifications that define pre- and post-conditions is emphasized to enable effective testing. Different types of testing like black box and white box are also discussed, along with common sources of errors like loops and conditional statements that should be considered during testing.
9.b-CMPS 403-F20-Session 9-Intro to ML II.pdf
This document provides an overview of machine learning concepts including:
1. It discusses different machine learning applications such as predicting age, identifying similar faces, and decision trees.
2. It covers machine learning issues like overfitting, the importance of generalization to new examples, and using a test set for evaluation.
3. It introduces neural networks including the basic structure of a perceptron, multi-layer perceptrons, backpropagation for training, and why deeper networks can be more powerful than shallow ones.
More Related Content
Similar to p1.pdf
DWX 2018 Session about Artificial Intelligence, Machine and Deep Learning
Artificial intelligence, machine learning, and deep learning provide benefits but also risks that should be addressed ethically and responsibly. AI has progressed due to exponential data growth, large unstructured datasets, improved hardware, and falling error rates. Deep learning in particular has advanced areas like computer vision, speech recognition and games. While concerns exist around a potential artificial general intelligence, AI also enables applications in healthcare, transportation, science and more. Individuals and companies are encouraged to start experimenting with and adopting machine learning.
Addis abeb university ..Artificial intelligence .pptx
The document defines artificial intelligence as the science and engineering of making intelligent machines, especially intelligent computer programs. It discusses that AI is the creation of computer programs that can learn to think and function on their own. The document then provides examples of technologies that use AI, such as machine learning, robotics, and neural networks. It describes the different types of AI as artificial narrow intelligence, artificial general intelligence, and artificial super intelligence. The document also outlines the history of AI and discusses its applications in various domains like agriculture, healthcare, business, and education.
Artificial Intelligence
This Presentation will give you an overview about Artificial Intelligence : definition, advantages , disadvantages , benefits , applications .
We hope it to be useful .
Selected topics in Computer Science
This document provides an overview of selected topics in computer science, including artificial intelligence, robotics, machine learning, and the internet of things. It will cover these topics through a series of sessions, discussing introductions and basic concepts for each. The first session introduces AI and compares it to machine learning. Subsequent sessions will cover robotics and its types, applications of machine learning, and laws of robotics. Students will work on individual or group projects related to these topics.
AI - An overwiew - presentation.pptx
This document provides an overview of artificial intelligence (AI) presented by Dr. Jeyadeepa R. It begins with defining key terms like intelligence and AI. It then lists the objectives which include defining AI, listing its domains, outlining its history, differentiating human and artificial intelligence, explaining aspects of AI, classifying types of AI, and describing the need for and pros and cons of AI. The document provides details on the history and evolution of AI, achievements in the field, differences between human and artificial intelligence, central principles, types of AI classified by functionality and capabilities, and need and applications of AI. It concludes by thanking the audience.
Artificial Intelligence Report
This document provides a case study on Google DeepMind and artificial intelligence. It discusses DeepMind's work in machine learning, deep reinforcement learning, and its creation of AlphaGo which was able to defeat professional Go players. The document also briefly outlines DeepMind's work in healthcare by collaborating with hospitals to analyze medical scans and develop algorithms to differentiate healthy and cancerous tissues. However, DeepMind's data sharing agreement with the Royal Free London NHS Foundation Trust to access patient medical records without consent was controversial.
Technologies Demystified: Artificial Intelligence
This document provides an overview of artificial intelligence (AI) including definitions of different types of AI, a brief history of AI, potential application fields and use cases, and the future outlook for AI. It defines AI as ranging from everyday applications to self-driving cars. It discusses narrow AI, general AI, and superintelligence. The document also summarizes key milestones in the development of AI from 1955 to the present and potential opportunities and challenges of AI including automation, ethics, and politics. It provides examples of Austrian AI startups and their technologies. The outlook suggests that human-level AI may be achieved by 2040 and superintelligence by 2060 with impacts on robotics, climate change, human enhancement, and autonomous
Artificial intelligence
just hvae a look, m sure u whould lyk it...............................................................................................................................................................................its all about artificial machines.....................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
Future aspects of ai by rahul abhishek
This document discusses the future of artificial intelligence. It describes how AI is currently being used in fields like robotics, gaming, and healthcare. The document outlines that in the future, AI may be able to match or surpass human-level intelligence. It also discusses potential risks of advanced AI, such as artificial intelligences that do not have human-like motivations and may pursue goals that do not align with human values. The document concludes that accurately predicting the capabilities and impacts of future AI remains challenging.
Artificial intelligence introduction
Artificial intelligence (AI) aims to build intelligent machines that can perform tasks requiring human intelligence. The goals of AI are to better understand human intelligence by modeling it in computer programs, and to create useful programs that can perform expert tasks. Many disciplines contribute to AI including computer science, psychology, philosophy, linguistics, and biology. Typical AI problems involve both mundane tasks like shopping and expert tasks like medical diagnosis. Philosophical issues in AI include what intelligence is, whether machines can truly be intelligent, and if human intelligence can be reduced to rules and calculations. This module will cover AI programming, knowledge representation, search techniques, natural language processing, machine learning, intelligent agents, and knowledge engineering.
AI 3.0: Is it Finally Time for Artificial Intelligence and Sensor Networks to...
Artificial intelligence and sensor networks may now be poised to disrupt various industries and jobs. Recent advances in algorithms, sensors, data collection, mobile technology, and robotics have increased concerns about the potential threats of artificial superintelligence ending humanity. The rapid changes in science and technology could significantly impact jobs in the coming decades as AI and automation replace many human roles.
Cognitive computing
The document discusses cognitive computing, which relies on techniques like expert systems, statistics, and mathematical models to mimic human reasoning. Cognitive computing systems can handle uncertainties and complex problems through experience and learning. The key aspects are:
- Cognitive computing represents self-learning systems that use machine learning models to mimic the human brain.
- The "brain" of cognitive systems is the neural network, which underlies deep learning.
- Cognitive computing aims to simulate human thought to solve complex problems through data analysis, pattern recognition, and natural language processing like the human brain.
Artificial intelligence
Artificial Intelligence : The discipline that attempts to build entities that do perceive, understand, predict, manipulate the world around us which is manifestly much larger than us.
Artificial Intelligence.pptx
Artificial intelligence (AI) is defined as the intelligence exhibited by machines or software. It involves the study and design of intelligent agents that can perceive their environment and take actions to maximize their success. There are four schools of thought on AI: thinking humanly, thinking rationally, acting humanly, and acting rationally. AI draws from many fields including mathematics, computer science, philosophy, linguistics, psychology, economics, and sociology. Some applications of AI include smart search algorithms, natural language processing for tasks like machine translation and summarization, knowledge bases for expert systems and medical diagnosis, and machine learning for tasks like face recognition and autonomous vehicles.
Sesi 1-1 Pengantar AI.pdf
AI is the study of intelligent agents: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Major areas of AI research include reasoning, knowledge, planning, learning, natural language processing, perception and the ability to move and manipulate objects. Weak AI is limited to a specific task, while strong AI exhibits human-level intelligence across all cognitive tasks. The foundations of AI include philosophy, mathematics, psychology and linguistics. Notable AI milestones include Deep Blue defeating Kasparov at chess in 1997 and the development of expert systems, robotics, computer vision and natural language processing. Current trends include cognitive computing, which aims to develop systems that can perceive, learn, reason and assist
AI (E Group)-1.pptx
This document discusses artificial intelligence (AI) and its applications in education. It defines AI as the ability of computers to perform tasks typically requiring human intelligence. The document then provides a brief history of AI, explains why computers are well-suited for certain tasks, and lists some key characteristics of AI like deep learning and facial recognition. It describes three main types of AI - narrow/weak AI, general/strong AI, and super AI - and four types based on functionality: reactive machines, limited memory, theory of mind, and self-awareness. Finally, it outlines several future applications of AI in education like personalized learning, intelligent tutoring systems, automated grading, and predictive analytics.
AI Foundation, Challenges and Applications.pptx
The document discusses an introduction to artificial intelligence lecture. It defines AI as the power of machines to mimic human behavior. It outlines the history, purposes, and foundations of AI, including logic, mathematics, psychology, computer science, linguistics. Examples of AI applications discussed include chatbots, self-driving cars, face recognition, and robotics. The types of AI are described as weak, strong, and super AI. The components of AI discussed are learning, reasoning, problem solving, perception, and language understanding. Challenges and issues with AI like costs, unemployment, and lack of emotions are also covered.
Artificial intelligence
Artificial intelligence (AI) is a broad field that combines computer science, psychology, and philosophy with the goal of creating machines that can think like humans. AI aims to develop intelligent agents that can perceive their environment and take actions to maximize their success. The main fields of AI include machine vision, expert systems, and creating machines that can think rationally or act like humans. The goals of AI include solving complex problems, enhancing human and computer interactions, and developing the theory and practice of building intelligent machines.
A Seminar Report on Artificial Intelligence
This is a seminar report on Artificial Intelligence. This is mainly concerned for engineering projects & reports. This is actually done for presentation purpose.
Similar to p1.pdf (20)
DWX 2018 Session about Artificial Intelligence, Machine and Deep Learning
DWX 2018 Session about Artificial Intelligence, Machine and Deep Learning
project-report-on-artificial-intelligence_compress (1).pdf
project-report-on-artificial-intelligence_compress (1).pdf
Addis abeb university ..Artificial intelligence .pptx
Addis abeb university ..Artificial intelligence .pptx
AI 3.0: Is it Finally Time for Artificial Intelligence and Sensor Networks to...
AI 3.0: Is it Finally Time for Artificial Intelligence and Sensor Networks to...
More from AmirMohamedNabilSale
LecccccccccccccProgrammingLecture-09.pdf
The document discusses development, testing, and debugging of programs. It covers the differences between correctness testing, which detects errors by comparing actual and expected results, and debugging, which fixes errors found during testing. Broad categories of errors like syntax, runtime, and semantic errors are described. The importance of function specifications that define pre- and post-conditions is emphasized to enable effective testing. Different types of testing like black box and white box are also discussed, along with common sources of errors like loops and conditional statements that should be considered during testing.
9.b-CMPS 403-F20-Session 9-Intro to ML II.pdf
This document provides an overview of machine learning concepts including:
1. It discusses different machine learning applications such as predicting age, identifying similar faces, and decision trees.
2. It covers machine learning issues like overfitting, the importance of generalization to new examples, and using a test set for evaluation.
3. It introduces neural networks including the basic structure of a perceptron, multi-layer perceptrons, backpropagation for training, and why deeper networks can be more powerful than shallow ones.
6.c-CMPS 403-F19-Session 6-Resolution.pdf
This document discusses logical concepts such as logical equivalence, validity, satisfiability, and inference. It presents two main methods for logical proof: model checking and applying inference rules. Model checking involves evaluating sentences in all possible models, while applying inference rules involves deriving new sentences from old using sound rules like resolution. Resolution is complete for propositional logic and works by combining clauses that contain complementary literals. An example proof using resolution is provided to show logical implication.
3.b-CMPS 403-F20-Session 3-Solving CSP I.pdf
Backtracking search is an algorithm for solving constraint satisfaction problems (CSPs) that involves trying variable assignments one at a time while checking constraints, abandoning partial solutions ("backtracking") that violate constraints. The document discusses techniques for improving backtracking search such as constraint propagation methods like forward checking and arc consistency for detecting inconsistent values earlier, as well as variable and value ordering heuristics like minimum remaining values. While filtering techniques improve performance, constraint satisfaction problems remain NP-hard in general.
2.a-CMPS 403-F20-Session 2-Search Problems.pdf
This document discusses search problems and planning agents. It begins by defining reflex agents that choose actions based only on the current state, and planning agents that consider future consequences of actions. Planning agents must have a model of how the world changes in response to actions. The document then discusses representing search problems using state spaces, successor functions, start/goal states. It provides examples of path finding and dot eating problems represented as search problems. Finally, it discusses using search trees and graphs to systematically explore possible plans through state spaces to solve problems.
LectureNote2.pdf
This document discusses intelligent agents and their design. It covers key concepts like the agent-environment interaction, rationality, and the PEAS framework for specifying an agent's task. Examples of agent domains are given, like a vacuum cleaner world, windshield wiper, self-driving car, medical diagnosis, spam filtering, and tutoring. The document outlines how agents are autonomous software that perceive their environment and act rationally to achieve goals.
Lecture_1_matrix_operations.pdf
The document discusses matrices and their operations. It defines what a matrix is and notes that matrices can represent linear transformations. It also explains that matrices can be used to solve systems of linear equations. The document then covers various matrix operations like addition, subtraction, multiplication, and inversion. It defines common matrix types like identity and zero matrices.
ML_1.pdf
This document provides an introduction and overview of a machine learning course. It discusses the instructor's background and contact information. The syllabus outlines topics that will be covered, including supervised and unsupervised learning algorithms. Prerequisites for the course and recommended textbooks are also mentioned. The document concludes by discussing features that are important for machine learning models, such as being informative, independent, and simple.
Linux.pdf
This document provides information about "The Linux Command Line" book including its copyright, release history, table of contents, and introduction. The introduction explains that the book teaches why and how to use the Linux command line interface. It is intended for users familiar with legacy operating systems who want to learn the Linux command line. The book covers basic shell and command line tasks like file manipulation and navigation.
Linux_Commands.pdf
This document provides a summary of common Linux commands for getting system and user information, working with directories and files, and finding help documentation. Commands covered include uname, whoami, cal, date, man, ls, cd, and pwd for viewing system details, dates, manuals, listing and changing directories. The document is intended to teach basic Linux commands.
AI in covid 19 (1).pptx
The document presents two proposed models for detecting COVID-19 from X-ray images using artificial intelligence. The first model uses deep learning with data augmentation and preprocessing of X-ray images, evaluating different optimizers and activation functions. It achieves the best accuracy of 95.2% using Adam optimizer and LeakyReLU activation. The second model performs feature fusion of GLCM and CNN features, achieving 96.1% accuracy with a batch size of 128. Previous work on COVID-19 classification using methods like SVM and deep learning are also discussed. Future work can focus on expanding datasets and interpreting model results.
COVID-19 PowerPoint.pptx
This document describes CoviFast, a system for classifying chest x-ray images as normal, pneumonia, or COVID-19. It uses several deep learning models like ResNet-50, MobileNetV2, and VGG-16 that are ensemble together. The system preprocesses images, enhances them, segments regions of interest, and augments the dataset. It then trains the ensemble model and evaluates it on test images using metrics like accuracy, precision, recall, and F1-score. The system aims to help detect COVID-19 from chest x-rays since not everyone has access to RT-PCR tests.
ML_DT.pdf
The document discusses classification using decision trees. It begins by defining classification and supervised learning. It then outlines the three main steps in the classification process: model construction using a training set, model evaluation on a test set, and using the model to predict class labels for new data. The document focuses on decision tree induction, explaining how decision trees are constructed in a top-down recursive manner by splitting nodes based on attribute values. It discusses measures like information gain and Gini index that are used to select the optimal attribute at each node split. The document also covers potential issues like overfitting and techniques like cross-validation to address them.
2.pdf
The document discusses intelligent agents and their design for artificial intelligence applications. It defines agents as perceiving their environment through sensors and acting through actuators. Additionally, it covers different types of agents including simple reflex agents, model-based reflex agents, goal-based agents, and utility-based agents as well as considerations for agent and environment design.
More from AmirMohamedNabilSale (18)
Recently uploaded
End-to-end pipeline agility - Berlin Buzzwords 2024
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
DSSML24_tspann_CodelessGenerativeAIPipelines
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
一比一原版(Harvard毕业证书)哈佛大学毕业证如何办理
毕业原版【微信:41543339】【(Harvard毕业证书)哈佛大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
学校原件一模一样【微信：741003700 】《(英国UCA毕业证书)创意艺术大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
毕业原版【微信:176555708】【(UCSF毕业证书)旧金山分校毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
by
Timothy Spann
Principal Developer Advocate
https://budapestdata.hu/2024/en/
https://budapestml.hu/2024/en/
tim.spann@zilliz.com
https://www.linkedin.com/in/timothyspann/
https://x.com/paasdev
https://github.com/tspannhw
https://www.youtube.com/@flank-stack
milvus
vector database
gen ai
generative ai
deep learning
machine learning
apache nifi
apache pulsar
apache kafka
apache flink
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
原版一模一样【微信：741003700 】【(uts毕业证书)悉尼科技大学毕业证学历证书】【微信：741003700 】学位证，留信认证（真实可查，永久存档）offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
毕业原版【微信:176555708】【(UMN毕业证书)明尼苏达大学毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
University of New South Wales degree offer diploma Transcript
澳洲UNSW毕业证书制作新南威尔士大学假文凭定制Q微168899991做UNSW留信网教留服认证海牙认证改UNSW成绩单GPA做UNSW假学位证假文凭高仿毕业证申请新南威尔士大学University of New South Wales degree offer diploma Transcript
Learn SQL from basic queries to Advance queries
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
Intelligence supported media monitoring in veterinary medicine
Media monitoring in veterinary medicien
State of Artificial intelligence Report 2023
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
Recently uploaded (20)
A presentation that explain the Power BI Licensing
A presentation that explain the Power BI Licensing
End-to-end pipeline agility - Berlin Buzzwords 2024
End-to-end pipeline agility - Berlin Buzzwords 2024
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
Influence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business Plan
University of New South Wales degree offer diploma Transcript
University of New South Wales degree offer diploma Transcript
Intelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicine
p1.pdf
- 1. Mansoura University Faculty of Computers and Information Course Name: Computer Science Lecturer: Amir EL-Ghamry Topic: Artificial intelligence
- 2. AI Artificial Intelligence a modern approach 2
- 3. AI Artificial Intelligence a modern approach 3 Anything made by human
- 4. AI Artificial Intelligence a modern approach 4 Ability to 1. Understand 2. Think 3. Learn
- 5. AI Artificial Intelligence a modern approach 5
- 6. AI Artificial Intelligence a modern approach 6 Artificial Intelligence (AI): A broad area of computer science that makes machines seem like have human intelligence
- 7. Artificial Intelligence a modern approach 7 Goal: Mimic human brain and create systems that can behave
- 8. Artificial Intelligence a modern approach 8
- 9. Artificial Intelligence a modern approach 9 AI expected to be little artificial and lot more intelligent
- 10. Artificial Intelligence a modern approach 10 AI will take role of intelligent workers
- 11. Artificial Intelligence a modern approach 11 Tasks will be automated using AI
- 12. 12 We will still need human experts who can build and maintain synthetic bots and Work on strategic and creative aspects of a job
- 13. 13
- 14. 14 AI + Humans VS problem statement