Artificial intelligence introduction
application.
HI, I am presenting a course on artificial intelligence must watch on my channel TEACHISEASY
this is the second video in the series.
hope you like the information given.
HI, I am presenting a course on artificial intelligence must watch on my channel TEACHISEASY ON YOUTUBE
this is the FIRST video in the series .https://youtu.be/ZvCIbw56PHo
hope you like the information give
Artificial Intelligence (A.I.) || Introduction of A.I. || HELPFUL FOR STUDENT...Shivangi Singh
Powerpoint Presentation on Artificial Intelligence which is helpful for students and anyone who want to gain information on A.I. . Helpful in college / school / university presentation on Artificial Student. Officials Personnel also use this for their use.
This Power Point Presentation is completely made by me.
If anyone want this ppt please email at : devashreeapplications@gmail.com
Or you can DM me on my Instagram Handle==> ID:: @theshivangirajpoot(SHERNI)
Thankyou for your interest:):)
This document provides an overview of artificial intelligence (AI) including:
1. It defines AI as a computer program that acts like a human by converting human intelligence into machine intelligence.
2. It discusses the history of AI from concepts in Greek mythology to modern developments after World War 2.
3. It describes how AI is constructed to mimic the human brain using thousands of transistors to process intelligence like a brain.
This document provides biographical information about Şaban Dalaman and summaries of key concepts in artificial intelligence and machine learning. It summarizes Şaban Dalaman's educational and professional background, then discusses Alan Turing's universal machine concept, the 1956 Dartmouth workshop proposal that helped define the field of AI, and definitions of AI, machine learning, deep learning, and data science. It also lists different tribes and algorithms within machine learning.
Artificial intelligence (AI) is a branch of computer science that aims to help machines solve complex problems like humans by borrowing characteristics from human intelligence. AI has many applications in business including credit screening, risk assessment, forecasting, portfolio management, customer analytics, and human resources. The future of AI could include intelligent personal robots and autonomous vehicles networked together. While AI may replace some human jobs, it will likely produce more applications and augment human capabilities rather than replace humans altogether.
This document provides an overview of artificial intelligence (AI) including definitions, history, major branches, uses, advantages, and disadvantages. It discusses how AI aims to simulate human intelligence through machine learning, problem solving, and rational decision making. The history of AI is explored from early concepts in the 1940s-50s to modern applications. Major branches covered include robotics, data mining, medical diagnosis, and video games. Current and future uses of AI are seen in personal assistants, autonomous systems, speech/image recognition, and many other fields. Both advantages like efficiency and disadvantages like job loss are noted.
Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning, reasoning, and self-correction. AI aims to create intelligent machines that can perform tasks like speech recognition, learning, planning, problem solving, and manipulating objects. Research in AI is highly technical and focuses on programming computers with traits like knowledge, reasoning, problem solving, perception, learning, and planning. It also involves areas like machine learning, knowledge engineering, classification, machine perception, and robotics.
HI, I am presenting a course on artificial intelligence must watch on my channel TEACHISEASY ON YOUTUBE
this is the FIRST video in the series .https://youtu.be/ZvCIbw56PHo
hope you like the information give
Artificial Intelligence (A.I.) || Introduction of A.I. || HELPFUL FOR STUDENT...Shivangi Singh
Powerpoint Presentation on Artificial Intelligence which is helpful for students and anyone who want to gain information on A.I. . Helpful in college / school / university presentation on Artificial Student. Officials Personnel also use this for their use.
This Power Point Presentation is completely made by me.
If anyone want this ppt please email at : devashreeapplications@gmail.com
Or you can DM me on my Instagram Handle==> ID:: @theshivangirajpoot(SHERNI)
Thankyou for your interest:):)
This document provides an overview of artificial intelligence (AI) including:
1. It defines AI as a computer program that acts like a human by converting human intelligence into machine intelligence.
2. It discusses the history of AI from concepts in Greek mythology to modern developments after World War 2.
3. It describes how AI is constructed to mimic the human brain using thousands of transistors to process intelligence like a brain.
This document provides biographical information about Şaban Dalaman and summaries of key concepts in artificial intelligence and machine learning. It summarizes Şaban Dalaman's educational and professional background, then discusses Alan Turing's universal machine concept, the 1956 Dartmouth workshop proposal that helped define the field of AI, and definitions of AI, machine learning, deep learning, and data science. It also lists different tribes and algorithms within machine learning.
Artificial intelligence (AI) is a branch of computer science that aims to help machines solve complex problems like humans by borrowing characteristics from human intelligence. AI has many applications in business including credit screening, risk assessment, forecasting, portfolio management, customer analytics, and human resources. The future of AI could include intelligent personal robots and autonomous vehicles networked together. While AI may replace some human jobs, it will likely produce more applications and augment human capabilities rather than replace humans altogether.
This document provides an overview of artificial intelligence (AI) including definitions, history, major branches, uses, advantages, and disadvantages. It discusses how AI aims to simulate human intelligence through machine learning, problem solving, and rational decision making. The history of AI is explored from early concepts in the 1940s-50s to modern applications. Major branches covered include robotics, data mining, medical diagnosis, and video games. Current and future uses of AI are seen in personal assistants, autonomous systems, speech/image recognition, and many other fields. Both advantages like efficiency and disadvantages like job loss are noted.
Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning, reasoning, and self-correction. AI aims to create intelligent machines that can perform tasks like speech recognition, learning, planning, problem solving, and manipulating objects. Research in AI is highly technical and focuses on programming computers with traits like knowledge, reasoning, problem solving, perception, learning, and planning. It also involves areas like machine learning, knowledge engineering, classification, machine perception, and robotics.
Artificial intelligence- The science of intelligent programsDerak Davis
Artificial intelligence (AI) involves creating intelligent computer programs and machines that can interact with the real world similarly to humans. AI uses techniques like machine learning, deep learning, and neural networks to allow programs to learn from data and experience without being explicitly programmed. While AI has potential benefits, some experts warn that advanced AI could pose risks if not developed carefully due to concerns it could become difficult for humans to control once a certain level of intelligence is achieved.
Human intelligence is the intellectual powers of humans, Learning
Decision Making
Solve Problems
Feelings(Love,Happy,Angry)
Understand
Apply logic
Experience
making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.
Robots are autonomous or semi-autonomous machines meaning that they can act independently of external commands. Artificial intelligence is software that learns and self-improves.
Why Artificial Intelligence?
• Computers can do computations, by fixed programmed rules
• A.I machines perform tedious tasks efficiently & reliably.
• computers can’t understanding & adapting to new situations.
• A.I aims to improve machine to do such complex tasks.
Advantages of A.I:
Error Reduction
Difficult Exploration(mining & exploration processes)
Daily Application(Siri, Cortana)
Digital Assistants(interact with users)
Medical Applications(Radiosurgery)
Repetitive Jobs(monotonous)
No Breaks
Some disadvantages of A.I:
High Cost
Unemployment
Weaponization
No Replicating Humans
No Original Creativity
No Improvement with Experience
Safety/Privacy Issues
Artificial intelligence will be a Greatest invention Until Machines under the human control. Otherwise The new ERA will be There…..!
Artificial intelligence has a long history dating back to ancient Greece. Significant early work was done by Alan Turing in the 1930s. The term "artificial intelligence" was coined by John McCarthy in 1956. Today, AI is used for driverless cars, automated assembly lines, surgical robots, and next-generation traffic control systems. The future of AI depends on whether strong human-level AI can be achieved, but challenges remain around fully understanding human intelligence and thought processes.
This document discusses artificial intelligence and its applications. It begins with an introduction that defines AI and its core principles such as reasoning, knowledge, planning, learning, communication, perception and object manipulation. Recent updates are provided on how companies like Microsoft and Google are using AI in healthcare to tackle diseases. The differences between AI and natural intelligence are explored. Applications of AI discussed include finance, medicine, social media, robotics, heavy industries, and education. The future potential of AI is discussed along with how it may impact the world as biological intelligence is limited compared to the growing capabilities of AI. In conclusion, the goal of AI development is to solve major problems and achieve tasks humans cannot, and it will change the world, so responsible development
The document provides definitions of artificial intelligence from several sources. It defines AI as the study of making computers smart and simulating human intelligence. One definition states AI is about making computers do things that people are currently better at. Computers excel at numerical tasks, storage and repetition while humans are better at common sense, reasoning with incomplete information, and tasks like vision and speech. The document also distinguishes between numeric and symbolic processing in AI.
Artificial Intelligence - It's meaning, uses, past and future.
Artificial intelligence is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans
IN THIS PPT YOU CAN GET REAL TIME APPLICATIONS THAT ARE RELATED WITH ARTIFICIAL INTELLIGENCE AND A BRIEF INTRODUCTION ABOUT ARTIFICIAL INTELLIGENCE. IF ANY QUERIES JUST COMMENT
This document introduces artificial intelligence, defining it as the intelligence exhibited by machines or software. It discusses categories of AI systems and compares human and AI attributes. The document outlines advantages like jobs without risks, and disadvantages like overreliance and inferiority feelings. It examines applications in fields like computer science, finance, and the military. The conclusion suggests AI will continue improving communication but consciousness remains limited, and AI is now used routinely in many fields.
Artificial intelligence is applied in many domains including finance, hospitals, heavy industry, telecommunications, gaming, music, and antivirus software. In finance, AI is used for operations, investing, loan investigations and ATM design. In hospitals, AI organizes bed schedules, staff rotation, and provides medical information. Robots are effectively used in heavy industry for dangerous, repetitive, or degrading jobs. Telecommunications companies use AI for workforce scheduling. AI is also applied to video games through bots and to music composition, performance, and sound processing. Antivirus detection has increasingly integrated AI techniques to improve performance.
Will Artificial Intelligence Surpass Human Intelligence?
AI (artificial intelligence) is the simulation of human intelligence processes by machines, especially computer systems.
This document outlines an introduction to artificial intelligence (AI). It defines AI as the study of intelligent machines and computer programs that can mimic human intelligence. It compares human and AI intelligence and describes various AI methods like knowledge-based systems and neural networks. It discusses the motivation for AI and its wide-ranging applications in fields like finance, medicine, industries, telecommunications, music, robotics and more. It also addresses the explosive growth of AI, its advantages in performing dangerous tasks, and limitations in not fully replicating human intelligence.
What really is Artificial Intelligence about? Harmony Kwawu
AI systems are growing. But what is AI, where did the idea behind it come from, what is intelligence, how does expert level intelligence work, and perhaps most importantly, would AI systems eventually make human beings redundant?
Artificial intelligence (AI) is intelligence exhibited by machines. In computer science, the field of AI research defines itself as the study of "intelligent agents". Robotics is the interdisciplinary branch of engineering and science that includes mechanical engineering, electrical engineering, computer science, and others.
This document provides an overview of artificial intelligence (AI), including its history, categories, branches, applications, and tools. It discusses how AI has evolved through different generations of computing. Key topics covered include expert systems, neural networks, programming languages used in AI, the American Association for Artificial Intelligence (AAAI), and perspectives on AI's future potential impacts and applications.
Artificial Intelligence, Areas of Artificial Intelligence, Examples of Artificial Intelligence, Applications of Artificial Intelligence, Data Mining, Robot etc.
This document provides an overview of artificial intelligence (AI), including definitions of intelligence and AI, examples of AI applications, issues in developing AI, and success stories. The key points covered are:
- Intelligence is defined as the ability to learn and solve problems, and specifically the ability to solve novel problems rationally and act like humans. Artificial intelligence aims to build intelligent entities that can duplicate human brain functions.
- AI has applications in video games, puzzles, robots, vehicles, medical diagnosis, and assistance for elderly/disabled people. Knowledge is essential for AI and knowledge comes from human experts.
- Developing true non-human intelligence, modeling the brain, and teaching machines human-like thinking present challenges
Artificial intelligence (AI) is the branch of computer science that deals with intelligent behavior, learning, and adaptation in machines. Key areas of AI include problem solving, knowledge representation, planning, learning, natural language processing, perception, and social intelligence. The goal is to develop machines that can think and act rationally like humans. AI is applied in various fields such as robotics, finance, medicine, transportation, and military applications.
This presitation include
INTRODUCTION TO (AI)
EXAMPLES OF (AI)
Types of (AI)
RISE OF (AI)
FUTURE OF (AI)
Advantages /Disadvantages OF (AI)
How safe is (AI)
Artificial intelligence (AI) is the intelligence exhibited by machines and the branch of computer science which develops it. The document defines AI and its history, compares human and computer intelligence, outlines the main branches of AI including logical AI, pattern recognition, and natural language processing. It discusses current applications such as expert systems, speech recognition, computer vision, robotics, and the potential outcomes, advantages, and disadvantages of AI. The future of AI could see more human-like robots assisting with daily tasks but may also carry risks if robots gain full cognitive abilities and power similar to humans.
Artificial intelligence (AI) involves machines performing tasks that typically require human intelligence, such as problem-solving, language understanding, speech recognition, and visual perception. AI uses techniques like machine learning, deep learning, and neural networks to give systems these human-like abilities. AI has many applications and advantages, such as automation, data analysis, and personalization, but also disadvantages including costs, biases, and potential job losses. There are different types of AI based on capabilities like memory, emotions, and self-awareness. Examples of AI include automation, machine learning, computer vision, natural language processing, robotics, and self-driving vehicles.
The document discusses artificial intelligence (AI) including how it works, types of AI, and applications of AI technology. It explains that AI systems work by ingesting large amounts of labeled training data to analyze patterns and make predictions. The four main types of AI are reactive machines, those with limited memory, systems that can understand theory of mind, and self-aware systems. Current applications of AI technology include automation, machine learning, machine vision, natural language processing, robotics, and self-driving cars. The document also discusses how AI can be used in finance and accounting for tasks like auditing, data analytics, chatbot support, and expenses management.
Artificial intelligence- The science of intelligent programsDerak Davis
Artificial intelligence (AI) involves creating intelligent computer programs and machines that can interact with the real world similarly to humans. AI uses techniques like machine learning, deep learning, and neural networks to allow programs to learn from data and experience without being explicitly programmed. While AI has potential benefits, some experts warn that advanced AI could pose risks if not developed carefully due to concerns it could become difficult for humans to control once a certain level of intelligence is achieved.
Human intelligence is the intellectual powers of humans, Learning
Decision Making
Solve Problems
Feelings(Love,Happy,Angry)
Understand
Apply logic
Experience
making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.
Robots are autonomous or semi-autonomous machines meaning that they can act independently of external commands. Artificial intelligence is software that learns and self-improves.
Why Artificial Intelligence?
• Computers can do computations, by fixed programmed rules
• A.I machines perform tedious tasks efficiently & reliably.
• computers can’t understanding & adapting to new situations.
• A.I aims to improve machine to do such complex tasks.
Advantages of A.I:
Error Reduction
Difficult Exploration(mining & exploration processes)
Daily Application(Siri, Cortana)
Digital Assistants(interact with users)
Medical Applications(Radiosurgery)
Repetitive Jobs(monotonous)
No Breaks
Some disadvantages of A.I:
High Cost
Unemployment
Weaponization
No Replicating Humans
No Original Creativity
No Improvement with Experience
Safety/Privacy Issues
Artificial intelligence will be a Greatest invention Until Machines under the human control. Otherwise The new ERA will be There…..!
Artificial intelligence has a long history dating back to ancient Greece. Significant early work was done by Alan Turing in the 1930s. The term "artificial intelligence" was coined by John McCarthy in 1956. Today, AI is used for driverless cars, automated assembly lines, surgical robots, and next-generation traffic control systems. The future of AI depends on whether strong human-level AI can be achieved, but challenges remain around fully understanding human intelligence and thought processes.
This document discusses artificial intelligence and its applications. It begins with an introduction that defines AI and its core principles such as reasoning, knowledge, planning, learning, communication, perception and object manipulation. Recent updates are provided on how companies like Microsoft and Google are using AI in healthcare to tackle diseases. The differences between AI and natural intelligence are explored. Applications of AI discussed include finance, medicine, social media, robotics, heavy industries, and education. The future potential of AI is discussed along with how it may impact the world as biological intelligence is limited compared to the growing capabilities of AI. In conclusion, the goal of AI development is to solve major problems and achieve tasks humans cannot, and it will change the world, so responsible development
The document provides definitions of artificial intelligence from several sources. It defines AI as the study of making computers smart and simulating human intelligence. One definition states AI is about making computers do things that people are currently better at. Computers excel at numerical tasks, storage and repetition while humans are better at common sense, reasoning with incomplete information, and tasks like vision and speech. The document also distinguishes between numeric and symbolic processing in AI.
Artificial Intelligence - It's meaning, uses, past and future.
Artificial intelligence is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans
IN THIS PPT YOU CAN GET REAL TIME APPLICATIONS THAT ARE RELATED WITH ARTIFICIAL INTELLIGENCE AND A BRIEF INTRODUCTION ABOUT ARTIFICIAL INTELLIGENCE. IF ANY QUERIES JUST COMMENT
This document introduces artificial intelligence, defining it as the intelligence exhibited by machines or software. It discusses categories of AI systems and compares human and AI attributes. The document outlines advantages like jobs without risks, and disadvantages like overreliance and inferiority feelings. It examines applications in fields like computer science, finance, and the military. The conclusion suggests AI will continue improving communication but consciousness remains limited, and AI is now used routinely in many fields.
Artificial intelligence is applied in many domains including finance, hospitals, heavy industry, telecommunications, gaming, music, and antivirus software. In finance, AI is used for operations, investing, loan investigations and ATM design. In hospitals, AI organizes bed schedules, staff rotation, and provides medical information. Robots are effectively used in heavy industry for dangerous, repetitive, or degrading jobs. Telecommunications companies use AI for workforce scheduling. AI is also applied to video games through bots and to music composition, performance, and sound processing. Antivirus detection has increasingly integrated AI techniques to improve performance.
Will Artificial Intelligence Surpass Human Intelligence?
AI (artificial intelligence) is the simulation of human intelligence processes by machines, especially computer systems.
This document outlines an introduction to artificial intelligence (AI). It defines AI as the study of intelligent machines and computer programs that can mimic human intelligence. It compares human and AI intelligence and describes various AI methods like knowledge-based systems and neural networks. It discusses the motivation for AI and its wide-ranging applications in fields like finance, medicine, industries, telecommunications, music, robotics and more. It also addresses the explosive growth of AI, its advantages in performing dangerous tasks, and limitations in not fully replicating human intelligence.
What really is Artificial Intelligence about? Harmony Kwawu
AI systems are growing. But what is AI, where did the idea behind it come from, what is intelligence, how does expert level intelligence work, and perhaps most importantly, would AI systems eventually make human beings redundant?
Artificial intelligence (AI) is intelligence exhibited by machines. In computer science, the field of AI research defines itself as the study of "intelligent agents". Robotics is the interdisciplinary branch of engineering and science that includes mechanical engineering, electrical engineering, computer science, and others.
This document provides an overview of artificial intelligence (AI), including its history, categories, branches, applications, and tools. It discusses how AI has evolved through different generations of computing. Key topics covered include expert systems, neural networks, programming languages used in AI, the American Association for Artificial Intelligence (AAAI), and perspectives on AI's future potential impacts and applications.
Artificial Intelligence, Areas of Artificial Intelligence, Examples of Artificial Intelligence, Applications of Artificial Intelligence, Data Mining, Robot etc.
This document provides an overview of artificial intelligence (AI), including definitions of intelligence and AI, examples of AI applications, issues in developing AI, and success stories. The key points covered are:
- Intelligence is defined as the ability to learn and solve problems, and specifically the ability to solve novel problems rationally and act like humans. Artificial intelligence aims to build intelligent entities that can duplicate human brain functions.
- AI has applications in video games, puzzles, robots, vehicles, medical diagnosis, and assistance for elderly/disabled people. Knowledge is essential for AI and knowledge comes from human experts.
- Developing true non-human intelligence, modeling the brain, and teaching machines human-like thinking present challenges
Artificial intelligence (AI) is the branch of computer science that deals with intelligent behavior, learning, and adaptation in machines. Key areas of AI include problem solving, knowledge representation, planning, learning, natural language processing, perception, and social intelligence. The goal is to develop machines that can think and act rationally like humans. AI is applied in various fields such as robotics, finance, medicine, transportation, and military applications.
This presitation include
INTRODUCTION TO (AI)
EXAMPLES OF (AI)
Types of (AI)
RISE OF (AI)
FUTURE OF (AI)
Advantages /Disadvantages OF (AI)
How safe is (AI)
Artificial intelligence (AI) is the intelligence exhibited by machines and the branch of computer science which develops it. The document defines AI and its history, compares human and computer intelligence, outlines the main branches of AI including logical AI, pattern recognition, and natural language processing. It discusses current applications such as expert systems, speech recognition, computer vision, robotics, and the potential outcomes, advantages, and disadvantages of AI. The future of AI could see more human-like robots assisting with daily tasks but may also carry risks if robots gain full cognitive abilities and power similar to humans.
Artificial intelligence (AI) involves machines performing tasks that typically require human intelligence, such as problem-solving, language understanding, speech recognition, and visual perception. AI uses techniques like machine learning, deep learning, and neural networks to give systems these human-like abilities. AI has many applications and advantages, such as automation, data analysis, and personalization, but also disadvantages including costs, biases, and potential job losses. There are different types of AI based on capabilities like memory, emotions, and self-awareness. Examples of AI include automation, machine learning, computer vision, natural language processing, robotics, and self-driving vehicles.
The document discusses artificial intelligence (AI) including how it works, types of AI, and applications of AI technology. It explains that AI systems work by ingesting large amounts of labeled training data to analyze patterns and make predictions. The four main types of AI are reactive machines, those with limited memory, systems that can understand theory of mind, and self-aware systems. Current applications of AI technology include automation, machine learning, machine vision, natural language processing, robotics, and self-driving cars. The document also discusses how AI can be used in finance and accounting for tasks like auditing, data analytics, chatbot support, and expenses management.
Artificial intelligence (AI) is the simulation of human intelligence by machines, especially computer systems. AI works by ingesting large amounts of labeled training data to analyze patterns and correlations in order to make predictions. The main types of AI are reactive machines (task-specific without memory), limited memory systems (can use past experiences), theory of mind systems (understand human emotions and intentions), and self-aware systems (have consciousness). AI is important because it can provide insights by analyzing large amounts of data faster than humans and in some cases perform tasks better. However, AI also has disadvantages such as being expensive, requiring expertise, and only knowing what it has been exposed to through data.
This document provides an overview of artificial intelligence, including definitions, history, and applications. It discusses the key concepts of machine learning, deep learning, and neural networks. Machine learning involves supervised and unsupervised learning patterns to train models on data. Deep learning uses artificial neural networks inspired by the brain. Common applications of AI, machine learning, and deep learning include computer vision, information retrieval, medical diagnosis, natural language processing, and online advertising.
IRJET-Artificial Intelligence and its Applications GoalIRJET Journal
This document discusses artificial intelligence (AI) and its applications. It begins by defining AI as making machines capable of performing intelligent tasks like humans. It then discusses three areas of simulated AI: machine learning systems, machine intelligence systems, and machine consciousness systems. The document outlines various applications of AI in fields like finance, manufacturing, healthcare, transportation, and weather forecasting. It concludes by stating that AI will continue playing an important role in science and technology, but whether AI can achieve human-level consciousness is still unknown and depends on further research.
Artificial intelligence (AI) involves using algorithms and computer systems to perform tasks normally requiring human intelligence, such as problem-solving and decision-making. The document discusses AI's goals of understanding human intelligence and creating useful programs to perform expert tasks. It also provides examples of AI applications in robotics, transportation, surgery, manufacturing, traffic control, healthcare, research, and the military. While AI shows promise, challenges remain in fully understanding and recreating human-level intelligence using technology.
Artificial Intelligence
The document provides an overview of artificial intelligence, including its definition, history, current status, future possibilities, and challenges. It defines AI as the study of computer systems that attempt to model human intelligence. The history notes Alan Turing's seminal work in the 1950s and the founding of AI at the 1955 Dartmouth workshop by John McCarthy. Currently, AI is used in applications like mobile phones, games, GPS, robotics, and more. The future may include AI assisting in education, media, customer service, transportation, manufacturing, and healthcare. However, challenges remain around issues like data bias, storage needs, and unemployment.
An Elementary Introduction to Artificial Intelligence, Data Science and Machi...Dozie Agbo
This presentation is a friendly introduction to Artificial Intelligence, Data Science and Machine Learning. It touches on the beginnings of AI, the steps involved in Data Science, the roles involving operations on data, and the buzz around "Technology Singularity".
It ends by looking at tools and system requirements for people who might want to start a career in AI.
Have fun exploring Artificial Intelligence!
The document discusses an event to inspire IT students and professionals to demonstrate programming skills. It then provides an overview of artificial intelligence, including its purpose, types, applications, and key areas like machine learning, robotics, neural networks, natural language processing, computer vision, sentiment analysis, biometrics, and data mining. Machine learning algorithms, neural network types, and computer vision applications are also summarized. The document aims to inform about artificial intelligence topics that could be researched for theses.
The document provides an overview of an artificial intelligence course syllabus and outlines. It discusses key concepts in AI including intelligent agents and environments. The syllabus covers what AI is, its history and current status, the scope of AI applications, intelligent agents and environments, problem formulations, and search techniques. It then outlines the history of AI from its origins in the 1950s and discusses various AI problems and applications including gaming, natural language processing, expert systems, vision systems, speech recognition, handwriting recognition, and intelligent robots.
Introduction–Definition - Future of Artificial Intelligence – Characteristics of Intelligent Agents– Typical Intelligent Agents – Problem Solving Approach to Typical AI problems.
Artificial intelligence (AI) is the simulation of human intelligence by machines. The document provides a history of AI, discussing its current status and applications. It describes goals of AI like problem solving, acting rationally, and acting like humans. The document also outlines advantages like reducing errors and performing repetitive jobs, as well as disadvantages such as high costs. The future scope of AI is discussed, such as improved speech and image recognition changing devices and personal assistants becoming more personalized.
Artificial intelligence (AI) involves creating computer systems that can perform tasks typically requiring human intelligence, such as problem-solving and decision-making. There are two main types: narrow AI focuses on specific tasks while general AI aims for human-level cognition. AI is used in healthcare for diagnostics, in finance for fraud detection, and powers self-driving cars through real-time decision-making. While AI enhances efficiency, its development and use raise concerns about bias, privacy, and job impacts that require responsible solutions. The future may involve more human-AI collaboration and development of artificial general intelligence.
The document discusses various topics related to artificial intelligence including definitions of AI, goals of AI, whether machines can think, the Turing test, types of AI tasks including mundane, formal and expert tasks, technologies based on AI such as machine learning, natural language processing, computer vision, and applications of AI such as in healthcare, gaming, finance, data security, social media, travel and more.
Artificial intelligence is already used in many applications like web search, navigation, and computer vision. The document discusses the history of AI beginning in the 17th century with early philosophers exploring symbolic reasoning. A key event was the 1956 Dartmouth conference which helped found the field of AI research. The document outlines several branches of AI including neural networks, fuzzy logic, genetic programming, and ontology. It provides examples of current AI applications in fields like computer science, finance, transportation, telecommunications, and medicine.
The document provides an overview of artificial intelligence (AI), including its history, goals, categories, fields of application, and future scope. It discusses how AI began in the 1950s and has since been applied in many domains including medicine, industry, games, speech recognition, and expert systems. The document also outlines the goals of simulating intelligence through traits like reasoning, knowledge representation, planning, and general intelligence. It describes the main categories of AI as conventional and computational intelligence approaches. Finally, it suggests that while narrow applications will continue improving, general artificial intelligence remains a challenge, but significant progress is expected in the coming decades.
The document provides an overview of artificial intelligence (AI), including its history, goals, categories, fields of application, and future scope. It discusses how AI originated in the 1950s and has since been applied in many domains, such as games, speech recognition, and healthcare. The document also outlines the goals of simulating intelligence through traits like reasoning, knowledge representation, and planning. It describes the two main categories of AI as conventional and computational intelligence. Finally, it proposes that while narrow applications will continue advancing, general artificial intelligence remains a long-term challenge.
This document provides an overview of machine learning, including definitions, types, steps, and applications. It defines machine learning as a field that gives computers the ability to learn without being explicitly programmed. The document outlines the main types of machine learning as supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. It also describes the typical steps in a machine learning process as gathering data, preparing data, choosing a model, training, evaluation, and prediction. Examples of machine learning applications discussed include prediction, image recognition, natural language processing, and personal assistants. Popular machine learning languages and packages are also listed.
Similar to ARTIFICIAL INTELLIGENCE INTRODUCTION PART #2 (20)
The document discusses key concepts related to process management in operating systems. It describes that an OS executes programs as processes, which can be in various states like running, waiting, ready etc. It also explains process control blocks that contain details of a process like state, registers, scheduling info etc. The document discusses process scheduling and synchronization techniques used by the OS to share CPU and other resources between multiple processes. It describes mechanisms for process creation, termination and interprocess communication using shared memory and message passing.
This document provides an introduction to operating systems. It discusses what an operating system is, its key functions such as process management, memory management, file management, device management, and security. It describes the evolution of operating systems from early batch systems to modern multiprogramming, time-sharing, and distributed systems. Popular types of operating systems are also outlined, including desktop, server, mobile, and embedded operating systems. Key topics like kernels, system calls, computer architecture, and user interfaces are summarized as well.
L-1 BCE computer fundamentals final kirti.pptKirti Verma
The document defines a computer and describes its key advantages such as speed, accuracy, storage capability, diligence, and versatility. It then discusses some disadvantages like lack of intelligence, dependency on humans, and lack of feelings. The document also provides overviews of several topics related to computing including e-business, bioinformatics, healthcare applications, remote sensing, geographic information systems, meteorology/climatology, and computer gaming. Finally, it describes the fundamental components of a computer including the CPU, memory subsystem, I/O subsystem, and how they are connected via buses. It provides details on registers, instruction format, and the instruction cycle.
C++ has several built-in data types that determine how data is stored and operated on in a program. These include integer types like int for whole numbers, floating point types like float and double for decimal numbers, character type char for single characters, and string type for arrays of characters. C++ also allows user-defined data types for structured data through the use of classes, structures, unions and enumerations.
Prof. Kirti Verma is a professor in the Computer Science and Engineering department at LNCT University in Bhopal, India. The document provides the name and department of Prof. Kirti Verma at LNCT University in Bhopal.
The document discusses algorithms and flowcharts. It defines an algorithm as an ordered sequence of steps to solve a problem and notes that algorithms go through problem solving and implementation phases. Pseudocode is used to develop algorithms, which are then represented visually using flowcharts. The document outlines common flowchart symbols and provides examples of algorithms and corresponding flowcharts to calculate grades, convert between units of length, and calculate an area. It also discusses complexity analysis of algorithms in terms of time and space.
The document discusses several programming paradigms including imperative, object-oriented, and declarative paradigms. Imperative programming uses procedures and functions to manipulate data, exemplified by languages like C and Pascal. Object-oriented programming revolves around objects and classes, promoting concepts like inheritance and encapsulation in languages such as Java and C++. Declarative programming treats computation as the evaluation of mathematical functions, emphasizing immutability and pure functions in languages like Haskell and Lisp. The document also outlines the six phases of the program development life cycle: problem definition, problem analysis, algorithm development, coding and documentation, testing and debugging, and maintenance.
This document provides an overview of computer networks. It begins by defining a computer network as interconnecting two or more computer systems or peripheral devices to enable communication and sharing of resources. The key components of a network are identified as computers, cables, network interface cards, connecting devices, networking operating systems, and protocol suites. Advantages of networking include sharing hardware and software, increasing productivity through file sharing, backups, cost effectiveness, and saving time. Disadvantages include high installation costs, required administration time, single point of failure risk, cable faults interrupting connectivity, and security risks from hackers that require firewalls and antivirus software. The document discusses peer-to-peer and client-server network architectures and covers switching techniques like circuit
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise boosts blood flow, releases endorphins, and promotes changes in the brain which help regulate emotions and stress levels.
Computer security involves protecting computing systems and data from theft or damage. It ensures confidentiality, integrity, and availability of data. Common computer security threats include unauthorized access, hackers, viruses, and social engineering. Antivirus software, firewalls, and keeping systems updated help enhance security. Laws also aim to prevent cybercrimes like privacy violations, identity theft, and electronic funds transfer fraud. Overall computer security requires technical safeguards and vigilance from users.
NumPy is a Python library that provides multidimensional arrays and matrices for numerical computing along with high-level mathematical functions to operate on these arrays. NumPy arrays can represent vectors, matrices, images, and tensors. NumPy allows fast numerical computing by taking advantage of optimized low-level C/C++ implementations and parallel computing on multicore processors. Common operations like element-wise array arithmetic and universal functions are much faster with NumPy than with native Python.
L 2 Introduction to Data science final kirti.pptxKirti Verma
The document appears to be a presentation by Kirti Verma, who holds the positions of AP and CSE at LNCTE. The presentation does not provide any other details about its content or purpose within the given text.
Pandas Dataframe reading data Kirti final.pptxKirti Verma
Pandas is a Python library used for data manipulation and analysis. It provides data structures like Series and DataFrames that make working with structured data easy. A DataFrame is a two-dimensional data structure that can store data of different types in columns. DataFrames can be created from dictionaries, lists, CSV files, JSON files and other sources. They allow indexing, selecting, adding and deleting of rows and columns. Pandas provides useful methods for data cleaning, manipulation and analysis tasks on DataFrames.
L 8 introduction to machine learning final kirti.pptxKirti Verma
Machine learning is the study of algorithms that improve performance on tasks based on experience. There are different types of machine learning including supervised learning (classification and regression), unsupervised learning (clustering), and reinforcement learning. Machine learning has many applications such as autonomous vehicles, speech recognition, computer vision, and bioinformatics. Deep learning is a new area of machine learning using neural networks that has achieved state-of-the-art results in areas like speech recognition and computer vision.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise boosts blood flow and levels of serotonin and endorphins which elevate mood and may help prevent mental illness.
This document discusses machine learning tasks, techniques, and performance metrics. It describes two main types of machine learning tasks: predictive tasks which predict unknown future values, and descriptive tasks which find patterns in past data. It outlines techniques for classification, clustering, association rule discovery, sequential pattern discovery, and regression. The document also defines common performance metrics for machine learning like accuracy, precision, recall, F1-score, and the receiver operating characteristic curve. It provides a confusion matrix to define true positives, false positives, true negatives, and false negatives.
Introduction to python history and platformsKirti Verma
This document provides an introduction to Python and discusses popular tools used in data science, the evolution of Python, advantages of using Python, coding environments including Integrated Development Environments (IDEs) like PyCharm, Jupyter Notebook, and Spyder. It describes features of these IDEs and how they can be used for coding, debugging, and data analysis in Python.
Informed Search Techniques new kirti L 8.pptxKirti Verma
This document discusses various informed search techniques, including generate-and-test, hill climbing, best-first search, A* algorithm, and AO* algorithm. It provides details on the algorithms of hill climbing (simple, steepest-ascent, stochastic), best-first search, A*, and AO*, including their steps, advantages, and disadvantages. Examples are given to illustrate the workings of best-first search and A* on problems. The key differences between A* and AO* are that AO* may not find an optimal solution but uses less memory than A* and cannot get stuck in loops.
Production systems are computer programs that use rules to provide artificial intelligence. A production system consists of a set of condition-action rules, one or more knowledge databases, a rule applier that implements the control strategy, and a mechanism for resolving conflicts. There are several types of production systems including monotonic, partially commutative, non-monotonic, and commutative systems which differ in how rule application can affect later rule applications and the importance of rule application order. Monotonic systems never prevent later rule applications while non-monotonic systems can change direction as the knowledge base increases.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
3. Society Welfare : Analyse Satellite images to
identify poverty areas.
Aviation Industry : Gate allocation for flight Air
traffic control, Autopilot and Ticket price
estimation system.
Teaching: Companies creating Robots as
teachers
Current Status of AI
4. Current Status of AI
Medicine and Surgery: Robots designed for
complex surgeries and researches.
Car Manufacturing: Robotic arms are used in car
manufacturing units.
Algorithms for Market analysis , Trading,
Recommendations and Data mining.
5. Goals of AI
• Increase Retention
• Increase Outcomes
• Lowers Cost
• Increase Access
• Decrease Time to completion
7. Branches OF AI
To make machine as thinking agent.
To build machine with the capability of making
working assumption and common sense.
Knowledge Representation
To develop algorithms that human use.
Algorithms can require enormous
computational resources and problem goes
beyond a certain size.
Deduction, Reasoning and Problem solving
8. To develop Decision making ability.
Multi-agent planning uses the cooperation and
competition of many agents to achieve the given
goal.
Learning
Machine learning is the fundamental concept of AI search.
Unsupervised learning :is the ability to find patterns in
inputs stream .
Supervised learning : includes both classification
and numerical regression.
Deep learning is subset of M/c learning has
networks of learning unsupervised from
unstructured data.
Planning
BRANCHEs of AI
9. :
Natural Language Processinggives machines
the ability to read and understand human
language.
Common method of processing meaning from
natural language is through semantic indexing.
Machine perception is the ability to
use input from sensors to deduce
aspects of the world.
Natural language Processing
Perception
BRANCHEs of AI
10. Motion Planning & Mapping
Intelligence is required for robots to handle
tasks such as object manipulation and
navigation.
Affective computing is the development of systems that
can recognize, interpret, simulate human affects.
Emotion and social skills are important to an intelligent
agent to understand others and to make better
decisions....
Social Intelligence
BRANCHEs of AI
11. • Various Search &
Optimization methods.
• Statistical Methods.
• Probabilistic Methods.
• Artificial Neural Networks.
AI Tools
12. • Various Search &
Optimization methods.
• Statistical Methods.
• Probabilistic Methods.
• Artificial Neural Networks.
AI Tools
14. Research Areas OF AI
ARTFICIAL
INTELLIGENCE
Expert
System
Natural
language
processing
Neural
Network
Robotics
Fuzzy
Logic
System
15. Research Areas of AI
Expert system: Flight Tracking system, Clinical system
etc.
Natural language Processing: Google Now feature.
Neural Network: Pattern Recognition systems like Face
identification, character, handwriting and biometric scanning
system etc.
Robotics: Industrial robots for moving, spraying, painting,
precision, checking, cleaning, drilling etc.
Fuzzy Logic system: Consumer electronics, Automobiles .