The document is a presentation by Tekendra Nath Yogi on Unit 10: Capacity Planning. It outlines calculating storage and CPU requirements and continues across 15 slides, discussing introduction, content, homework, and concluding with thanks.
This document outlines a presentation by Tekendra Nath Yogi on data warehousing for a college course. The presentation covers extracting, transforming, and loading data from operational sources into a data warehouse, the processes and managers involved in data warehousing, guidelines for designing and implementing a data warehouse. The outline includes sections on operational data sources, ETL processes, data warehouse functions, design, and implementation guidelines.
This document outlines a presentation on information privacy and data mining. It discusses basic principles for protecting information privacy, the uses and misuses of data mining, the primary aims of data mining, and pitfalls of data mining. The presentation was created by Tekendra Nath Yogi for a college course and contains an introduction and multiple continuation pages.
The document outlines a unit on advanced applications in data mining, presenting topics like web mining, including web content and usage mining, and time-series data mining. It was created by Tekendra Nath Yogi for students in the College of Applied Business and Technology. The presentation continues across multiple slides with an introduction and content sections.
The document outlines a presentation on search engines given by Tekendra Nath Yogi. It discusses the characteristics of search engines, their functionality, and how they rank web pages. The presentation covers these topics over several slides and concludes by thanking the audience.
Not a long jumper — Greig Rutherford — Standard Life AberdeenIntranet Now
Making assumptions can take you into dangerous territory. That’s why Greig and the team undertook a digital diary exercise with their global workforce to ensure their views were central to creating their new digital workplace.
The document discusses expert systems, including their characteristics, components, and examples. It describes how expert systems use specialized knowledge to solve problems in a specific domain similar to a human expert. Classic expert systems like DENDRAL, MYCIN, and EMYCIN are discussed. Knowledge engineering and case-based reasoning are also summarized.
This document provides an overview of production systems. It defines the key components of a production system including production rules, working memory, and a recognize-act control cycle. Examples of forward and backward chaining are provided. Advantages such as the separation of knowledge and control and mapping to state space search are discussed. Conflict resolution strategies like refraction, recency and specificity are also summarized.
This document presents an overview of uncertainty in artificial intelligence, specifically focusing on fuzzy logic. It defines fuzzy logic as a way to deal with imprecise and vague information using degrees of truth rather than binary logic. The key concepts discussed include fuzzy sets and their operations, fuzzy rules and inferences, and applications of fuzzy logic systems. Examples are provided to illustrate fuzzy sets for describing tall men and an air conditioning system controlled by a fuzzy logic controller.
This document outlines a presentation by Tekendra Nath Yogi on data warehousing for a college course. The presentation covers extracting, transforming, and loading data from operational sources into a data warehouse, the processes and managers involved in data warehousing, guidelines for designing and implementing a data warehouse. The outline includes sections on operational data sources, ETL processes, data warehouse functions, design, and implementation guidelines.
This document outlines a presentation on information privacy and data mining. It discusses basic principles for protecting information privacy, the uses and misuses of data mining, the primary aims of data mining, and pitfalls of data mining. The presentation was created by Tekendra Nath Yogi for a college course and contains an introduction and multiple continuation pages.
The document outlines a unit on advanced applications in data mining, presenting topics like web mining, including web content and usage mining, and time-series data mining. It was created by Tekendra Nath Yogi for students in the College of Applied Business and Technology. The presentation continues across multiple slides with an introduction and content sections.
The document outlines a presentation on search engines given by Tekendra Nath Yogi. It discusses the characteristics of search engines, their functionality, and how they rank web pages. The presentation covers these topics over several slides and concludes by thanking the audience.
Not a long jumper — Greig Rutherford — Standard Life AberdeenIntranet Now
Making assumptions can take you into dangerous territory. That’s why Greig and the team undertook a digital diary exercise with their global workforce to ensure their views were central to creating their new digital workplace.
The document discusses expert systems, including their characteristics, components, and examples. It describes how expert systems use specialized knowledge to solve problems in a specific domain similar to a human expert. Classic expert systems like DENDRAL, MYCIN, and EMYCIN are discussed. Knowledge engineering and case-based reasoning are also summarized.
This document provides an overview of production systems. It defines the key components of a production system including production rules, working memory, and a recognize-act control cycle. Examples of forward and backward chaining are provided. Advantages such as the separation of knowledge and control and mapping to state space search are discussed. Conflict resolution strategies like refraction, recency and specificity are also summarized.
This document presents an overview of uncertainty in artificial intelligence, specifically focusing on fuzzy logic. It defines fuzzy logic as a way to deal with imprecise and vague information using degrees of truth rather than binary logic. The key concepts discussed include fuzzy sets and their operations, fuzzy rules and inferences, and applications of fuzzy logic systems. Examples are provided to illustrate fuzzy sets for describing tall men and an air conditioning system controlled by a fuzzy logic controller.
The document provides an overview of machine learning presented by Tekendra Nath Yogi. It defines machine learning and different types including supervised, unsupervised, and reinforced learning. Supervised learning algorithms like least mean square regression and gradient descent learning are explained. Unsupervised learning examples including clustering are provided. Reinforced learning emphasizes learning from feedback to maximize rewards. Backpropagation and artificial neural networks are also summarized. The document outlines key machine learning concepts in 15 slides.
This document outlines a presentation on knowledge representation. It begins with an introduction to propositional logic, including its syntax, semantics, and properties. Several inference methods for propositional logic are discussed, including truth tables, deductive systems, and resolution. Predicate logic and semantic networks are also mentioned as topics to be covered. The overall document provides an outline of the key concepts to be presented on knowledge representation using logic.
The document discusses various search algorithms used in artificial intelligence including uninformed and informed search methods. It provides details on breadth-first search, depth-first search, uniform cost search, and heuristic search approaches like hill climbing, greedy best-first search, and A* search. It also covers general problem solving techniques and evaluating search performance based on completeness, time complexity, space complexity, and optimality.
The document outlines various concepts related to agents and environments, including:
- Different types of agents such as rational agents, intelligent agents, simple reflex agents, model-based reflex agents, goal-based agents, and learning agents.
- Properties of environments including fully/partially observable, single/multi-agent, deterministic/stochastic, episodic/sequential, static/dynamic, discrete/continuous, and known/unknown.
- An example of a vacuum cleaning agent interacting with its environment is provided to illustrate agents, percepts, actions, and environments.
This document provides an overview of an Artificial Intelligence course. The course aims to introduce students to the broad field of AI and prepare them for opportunities in the AI field. It will cover topics like searching, knowledge representation, learning, neural networks, and applications of AI. The course objectives are to provide a basic foundation of concepts in searching and knowledge representation. Students will complete laboratory tasks involving predicate calculus, searching, and neural networks to apply their learning.
The document discusses artificial neural networks and their biological inspiration. It provides details on:
- The basic structure and functioning of biological neurons
- How artificial neural networks are modeled after biological neural networks with nodes, links, weights, and activation functions
- Examples of different activation functions used in artificial neurons like threshold, sigmoid, and linear functions
- How simple logic gates can be modeled using the McCulloch-Pitts neuron model with different weight configurations
- Learning in neural networks involves adjusting the connection weights between neurons through supervised or unsupervised learning processes.
This document summarizes a presentation on cluster analysis given by Tekendra Nath Yogi. It defines cluster analysis and describes several clustering methods and algorithms, including k-means clustering. It also discusses applications of cluster analysis in fields like business intelligence, image recognition, web search, and biology. Requirements for effective clustering algorithms are outlined.
This document outlines the process of association rule mining using the Apriori algorithm. It begins with definitions of key terms like frequent itemsets, support, and confidence. It then explains how the Apriori algorithm reduces the search space using the Apriori property to only consider potentially frequent itemsets. Finally, it provides examples applying the Apriori algorithm to transaction databases to generate strong association rules that meet minimum support and confidence thresholds.
classification algorithms, decision tree, naive bayes, back propagation, KNN,TU, BIM 8th semester Data mining and data warehousing Slide by Tekendra Nath Yogi
B. SC CSIT Computer Graphics Unit 5 By Tekendra Nath YogiTekendra Nath Yogi
Virtual reality and computer animation are introduced. Virtual reality uses head-mounted displays and sensors to generate realistic 3D environments that can provoke physical reactions from users. Computer animation is the technique of generating animated sequences through defining objects, keyframes, and generating in-between frames. Both virtual reality and computer animation have applications in entertainment, advertising, education, and scientific/engineering fields.
B. SC CSIT Computer Graphics Lab By Tekendra Nath YogiTekendra Nath Yogi
The document discusses computer graphics and summarizes various graphics programming concepts in C, including:
- Two standard output modes: text and graphics mode, which allows pixel manipulation.
- Graphics library functions defined in "graphics.h" header file for drawing shapes, text and manipulating pixels.
- Coordinate representation on screen with origin at upper left corner.
- Initialization of graphics mode using initgraph() and cleanup with closegraph().
- Functions for drawing lines, circles, rectangles, text and filling areas with patterns.
- Algorithms like DDA, Bresenham and midpoint circle/ellipse for drawing shapes.
B. SC CSIT Computer Graphics Unit 4 By Tekendra Nath YogiTekendra Nath Yogi
The document discusses various techniques for visible surface determination and surface rendering in 3D graphics. It covers algorithms like z-buffer, list priority, and scan line algorithms for visible surface detection. It also discusses illumination models, surface shading methods like Gouraud and Phong shading, and provides pseudocode examples for image space and object space visible surface determination methods. Specific algorithms covered in more detail include the back face detection, z-buffer, list priority, and scan line algorithms.
B. SC CSIT Computer Graphics Unit 3 By Tekendra Nath YogiTekendra Nath Yogi
This document discusses various methods for 3D object representation in computer graphics. It covers surface modeling techniques like polygon meshes, parametric cubic curves, and quadratic surfaces. It also discusses solid modeling representations such as sweep, boundary, and spatial partitioning. Additionally, it provides details on polygon mesh data structures, plane equations, quadric surfaces, and parametric cubic curves. Specifically, it explains how to define curves using parametric cubic functions and calculate coefficients for natural cubic splines.
B. SC CSIT Computer Graphics Unit 2 By Tekendra Nath YogiTekendra Nath Yogi
The document discusses various 2D and 3D geometric transformations including translation, rotation, scaling, and their implementations using matrix representations and homogeneous coordinates. It provides examples of translating, rotating, and scaling points and polygons. It also covers composite transformations, inverse transformations, and applications to 2D and 3D viewing. Homework examples are provided to practice applying the different transformation types.
B. SC CSIT Computer Graphics Unit 1.3 By Tekendra Nath YogiTekendra Nath Yogi
The document discusses different area filling algorithms such as scan-line filling, boundary filling, and flood filling. It describes how to fill shapes like rectangles and ellipses using these algorithms. For rectangle filling, it explains using either scan-line filling or boundary filling in a 4-connected or 8-connected approach. It also discusses filling areas with textures by mapping the texture pixels to the shape pixels. Homework questions are provided at the end to write procedures to implement an 8-way connected flood fill and ellipse filling with a pattern.
B. SC CSIT Computer Graphics Unit1.2 By Tekendra Nath YogiTekendra Nath Yogi
1. The document discusses raster graphics and algorithms for drawing basic 2D primitives like points, lines, circles, and polygons.
2. It describes two common line drawing algorithms - the Digital Differential Analyzer (DDA) algorithm and Bresenham's line algorithm.
3. The DDA algorithm draws lines by calculating pixel positions using the slope of the line, while Bresenham's algorithm uses only integer calculations to find the next pixel position along the line.
B. SC CSIT Computer Graphics Unit1.1 By Tekendra Nath YogiTekendra Nath Yogi
This document provides details about the Computer Graphics course CSC-254 taught by Mr. Tekendra Nath Yogi. The course is 3 credits and covers 5 units including introduction to computer graphics, geometrical transformations, 3D object representation, visible surface determination, and virtual reality and animation. It will also include laboratory works implementing algorithms in OpenGL. The course aims to provide an understanding of theoretical foundations of 2D and 3D graphics.
This document summarizes key aspects of templates and exception handling in C++. It discusses function and class templates, including how templates allow writing generic code to handle different data types. It also covers exception handling mechanisms like try, throw, and catch blocks, and how they are used to detect and handle runtime errors. Templates and exceptions handling are important C++ features that increase code reuse and make programs more robust.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
This presentation provides valuable insights into effective cost-saving techniques on AWS. Learn how to optimize your AWS resources by rightsizing, increasing elasticity, picking the right storage class, and choosing the best pricing model. Additionally, discover essential governance mechanisms to ensure continuous cost efficiency. Whether you are new to AWS or an experienced user, this presentation provides clear and practical tips to help you reduce your cloud costs and get the most out of your budget.
The document provides an overview of machine learning presented by Tekendra Nath Yogi. It defines machine learning and different types including supervised, unsupervised, and reinforced learning. Supervised learning algorithms like least mean square regression and gradient descent learning are explained. Unsupervised learning examples including clustering are provided. Reinforced learning emphasizes learning from feedback to maximize rewards. Backpropagation and artificial neural networks are also summarized. The document outlines key machine learning concepts in 15 slides.
This document outlines a presentation on knowledge representation. It begins with an introduction to propositional logic, including its syntax, semantics, and properties. Several inference methods for propositional logic are discussed, including truth tables, deductive systems, and resolution. Predicate logic and semantic networks are also mentioned as topics to be covered. The overall document provides an outline of the key concepts to be presented on knowledge representation using logic.
The document discusses various search algorithms used in artificial intelligence including uninformed and informed search methods. It provides details on breadth-first search, depth-first search, uniform cost search, and heuristic search approaches like hill climbing, greedy best-first search, and A* search. It also covers general problem solving techniques and evaluating search performance based on completeness, time complexity, space complexity, and optimality.
The document outlines various concepts related to agents and environments, including:
- Different types of agents such as rational agents, intelligent agents, simple reflex agents, model-based reflex agents, goal-based agents, and learning agents.
- Properties of environments including fully/partially observable, single/multi-agent, deterministic/stochastic, episodic/sequential, static/dynamic, discrete/continuous, and known/unknown.
- An example of a vacuum cleaning agent interacting with its environment is provided to illustrate agents, percepts, actions, and environments.
This document provides an overview of an Artificial Intelligence course. The course aims to introduce students to the broad field of AI and prepare them for opportunities in the AI field. It will cover topics like searching, knowledge representation, learning, neural networks, and applications of AI. The course objectives are to provide a basic foundation of concepts in searching and knowledge representation. Students will complete laboratory tasks involving predicate calculus, searching, and neural networks to apply their learning.
The document discusses artificial neural networks and their biological inspiration. It provides details on:
- The basic structure and functioning of biological neurons
- How artificial neural networks are modeled after biological neural networks with nodes, links, weights, and activation functions
- Examples of different activation functions used in artificial neurons like threshold, sigmoid, and linear functions
- How simple logic gates can be modeled using the McCulloch-Pitts neuron model with different weight configurations
- Learning in neural networks involves adjusting the connection weights between neurons through supervised or unsupervised learning processes.
This document summarizes a presentation on cluster analysis given by Tekendra Nath Yogi. It defines cluster analysis and describes several clustering methods and algorithms, including k-means clustering. It also discusses applications of cluster analysis in fields like business intelligence, image recognition, web search, and biology. Requirements for effective clustering algorithms are outlined.
This document outlines the process of association rule mining using the Apriori algorithm. It begins with definitions of key terms like frequent itemsets, support, and confidence. It then explains how the Apriori algorithm reduces the search space using the Apriori property to only consider potentially frequent itemsets. Finally, it provides examples applying the Apriori algorithm to transaction databases to generate strong association rules that meet minimum support and confidence thresholds.
classification algorithms, decision tree, naive bayes, back propagation, KNN,TU, BIM 8th semester Data mining and data warehousing Slide by Tekendra Nath Yogi
B. SC CSIT Computer Graphics Unit 5 By Tekendra Nath YogiTekendra Nath Yogi
Virtual reality and computer animation are introduced. Virtual reality uses head-mounted displays and sensors to generate realistic 3D environments that can provoke physical reactions from users. Computer animation is the technique of generating animated sequences through defining objects, keyframes, and generating in-between frames. Both virtual reality and computer animation have applications in entertainment, advertising, education, and scientific/engineering fields.
B. SC CSIT Computer Graphics Lab By Tekendra Nath YogiTekendra Nath Yogi
The document discusses computer graphics and summarizes various graphics programming concepts in C, including:
- Two standard output modes: text and graphics mode, which allows pixel manipulation.
- Graphics library functions defined in "graphics.h" header file for drawing shapes, text and manipulating pixels.
- Coordinate representation on screen with origin at upper left corner.
- Initialization of graphics mode using initgraph() and cleanup with closegraph().
- Functions for drawing lines, circles, rectangles, text and filling areas with patterns.
- Algorithms like DDA, Bresenham and midpoint circle/ellipse for drawing shapes.
B. SC CSIT Computer Graphics Unit 4 By Tekendra Nath YogiTekendra Nath Yogi
The document discusses various techniques for visible surface determination and surface rendering in 3D graphics. It covers algorithms like z-buffer, list priority, and scan line algorithms for visible surface detection. It also discusses illumination models, surface shading methods like Gouraud and Phong shading, and provides pseudocode examples for image space and object space visible surface determination methods. Specific algorithms covered in more detail include the back face detection, z-buffer, list priority, and scan line algorithms.
B. SC CSIT Computer Graphics Unit 3 By Tekendra Nath YogiTekendra Nath Yogi
This document discusses various methods for 3D object representation in computer graphics. It covers surface modeling techniques like polygon meshes, parametric cubic curves, and quadratic surfaces. It also discusses solid modeling representations such as sweep, boundary, and spatial partitioning. Additionally, it provides details on polygon mesh data structures, plane equations, quadric surfaces, and parametric cubic curves. Specifically, it explains how to define curves using parametric cubic functions and calculate coefficients for natural cubic splines.
B. SC CSIT Computer Graphics Unit 2 By Tekendra Nath YogiTekendra Nath Yogi
The document discusses various 2D and 3D geometric transformations including translation, rotation, scaling, and their implementations using matrix representations and homogeneous coordinates. It provides examples of translating, rotating, and scaling points and polygons. It also covers composite transformations, inverse transformations, and applications to 2D and 3D viewing. Homework examples are provided to practice applying the different transformation types.
B. SC CSIT Computer Graphics Unit 1.3 By Tekendra Nath YogiTekendra Nath Yogi
The document discusses different area filling algorithms such as scan-line filling, boundary filling, and flood filling. It describes how to fill shapes like rectangles and ellipses using these algorithms. For rectangle filling, it explains using either scan-line filling or boundary filling in a 4-connected or 8-connected approach. It also discusses filling areas with textures by mapping the texture pixels to the shape pixels. Homework questions are provided at the end to write procedures to implement an 8-way connected flood fill and ellipse filling with a pattern.
B. SC CSIT Computer Graphics Unit1.2 By Tekendra Nath YogiTekendra Nath Yogi
1. The document discusses raster graphics and algorithms for drawing basic 2D primitives like points, lines, circles, and polygons.
2. It describes two common line drawing algorithms - the Digital Differential Analyzer (DDA) algorithm and Bresenham's line algorithm.
3. The DDA algorithm draws lines by calculating pixel positions using the slope of the line, while Bresenham's algorithm uses only integer calculations to find the next pixel position along the line.
B. SC CSIT Computer Graphics Unit1.1 By Tekendra Nath YogiTekendra Nath Yogi
This document provides details about the Computer Graphics course CSC-254 taught by Mr. Tekendra Nath Yogi. The course is 3 credits and covers 5 units including introduction to computer graphics, geometrical transformations, 3D object representation, visible surface determination, and virtual reality and animation. It will also include laboratory works implementing algorithms in OpenGL. The course aims to provide an understanding of theoretical foundations of 2D and 3D graphics.
This document summarizes key aspects of templates and exception handling in C++. It discusses function and class templates, including how templates allow writing generic code to handle different data types. It also covers exception handling mechanisms like try, throw, and catch blocks, and how they are used to detect and handle runtime errors. Templates and exceptions handling are important C++ features that increase code reuse and make programs more robust.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
This presentation provides valuable insights into effective cost-saving techniques on AWS. Learn how to optimize your AWS resources by rightsizing, increasing elasticity, picking the right storage class, and choosing the best pricing model. Additionally, discover essential governance mechanisms to ensure continuous cost efficiency. Whether you are new to AWS or an experienced user, this presentation provides clear and practical tips to help you reduce your cloud costs and get the most out of your budget.
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...alexjohnson7307
Predictive maintenance is a proactive approach that anticipates equipment failures before they happen. At the forefront of this innovative strategy is Artificial Intelligence (AI), which brings unprecedented precision and efficiency. AI in predictive maintenance is transforming industries by reducing downtime, minimizing costs, and enhancing productivity.
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Nunit vs XUnit vs MSTest Differences Between These Unit Testing Frameworks.pdfflufftailshop
When it comes to unit testing in the .NET ecosystem, developers have a wide range of options available. Among the most popular choices are NUnit, XUnit, and MSTest. These unit testing frameworks provide essential tools and features to help ensure the quality and reliability of code. However, understanding the differences between these frameworks is crucial for selecting the most suitable one for your projects.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
A Comprehensive Guide to DeFi Development Services in 2024Intelisync
DeFi represents a paradigm shift in the financial industry. Instead of relying on traditional, centralized institutions like banks, DeFi leverages blockchain technology to create a decentralized network of financial services. This means that financial transactions can occur directly between parties, without intermediaries, using smart contracts on platforms like Ethereum.
In 2024, we are witnessing an explosion of new DeFi projects and protocols, each pushing the boundaries of what’s possible in finance.
In summary, DeFi in 2024 is not just a trend; it’s a revolution that democratizes finance, enhances security and transparency, and fosters continuous innovation. As we proceed through this presentation, we'll explore the various components and services of DeFi in detail, shedding light on how they are transforming the financial landscape.
At Intelisync, we specialize in providing comprehensive DeFi development services tailored to meet the unique needs of our clients. From smart contract development to dApp creation and security audits, we ensure that your DeFi project is built with innovation, security, and scalability in mind. Trust Intelisync to guide you through the intricate landscape of decentralized finance and unlock the full potential of blockchain technology.
Ready to take your DeFi project to the next level? Partner with Intelisync for expert DeFi development services today!
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen