Foundations Of A.I.: Search Algorithms - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Foundations Of A.I.: Search Algorithms (/Thread-Foundations-Of-A-I-Search-Algorithms) |
Foundations Of A.I.: Search Algorithms - nieriorefasow63 - 12-20-2023 Foundations Of A.I.: Search Algorithms Published 12/2023 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 2.74 GB | Duration: 4h 19m Search Algorithms What you'll learn Definition of A.I. Definition of A.I. Search Algorithms Elements of Graph Search Optimization Requirements Basic Understanding of Programming Python Fundamentals Description This course is designed for all enthusiasts who are interested for a career in Artificial Intelligence. The main objective of this course is to give a solid foundation of the good old Artificial Intelligence concepts which includes the definition of Artificial Intelligence, different schools of Thought, a tinge of Sir Alan Turing's thoughts about Computational Thinking. As we progress into the course, we will try to understand the significance of graphs and how any problem can be represented as a Graph. At the heart of this course is Search Algorithms, we will have a look at methods that allow computers to search for solution in a huge solution space. In that pursuit, we will work with Uninformed Search and Informed Search Algorithms. Informed Search algorithms have their foot print in Robotics, Navigation systems, designing games and many more. Course is incomplete if we leave with informed search, to counter the problems of search algorithms, we will look into local search which will eventually land in Optimization. In local search, we will work with Hill climbing algorithms along with their disadvantages. To sum up, this course gives answers to questions raised by students who want to explore the fundamentals difference between human intelligence and machine intelligence. Overview Section 1: About the Program Lecture 1 Course Introduction Lecture 2 Course Outline Section 2: What is Artificial Intelligence? Lecture 3 Where is A.I. Around Us? Lecture 4 What is A.I.? Lecture 5 A.I. Paradigms Lecture 6 Why A.I. is Important Now? Lecture 7 Applications of A.I. Lecture 8 History of A.I. Lecture 9 How does Human Intelligence Work? Section 3: Rationality, Agents & Environment Lecture 10 What is an Agent and Environment? Lecture 11 What is Rationality and a Rational Agent? Lecture 12 Factors of Rationality Lecture 13 Nature of Environments Lecture 14 Types of Agent Architectures Lecture 15 Simple Reflex Agent Lecture 16 Reflex Agent with Internal State Lecture 17 Goal based Agent Lecture 18 Utility based Agents Section 4: Software Installation Lecture 19 Installing Anaconda Distribution Lecture 20 Handling Jupyter Notebooks 1 Lecture 21 Handling Jupyter Notebooks 2 Section 5: Python Crash Course Lecture 22 What is Python? Lecture 23 Data Types in Python Lecture 24 Loops-For (Jupyter) Lecture 25 Loops-While (Jupyter) Lecture 26 Creating Functions in Python (Jupyter) Lecture 27 Conditional Statements - If Else (Jupyter) Section 6: Problem Solving Lecture 28 What is a Problem? Lecture 29 Problem Solving Agent Lecture 30 Search Algorithms Lecture 31 Introduction to Graph Search Lecture 32 Elements of Graph Search Lecture 33 Types of Search Algorithms Section 7: Search Algorithms-Uninformed Search Lecture 34 Uninformed Search Algorithms Lecture 35 Breadth First Search Lecture 36 Implementation of Breadth First Search in Python Lecture 37 Depth First Search Lecture 38 Implementation of Depth First Search in Python Lecture 39 Depth Limited Search Lecture 40 Iterative Deepening Search Lecture 41 Uniform Cost Search Section 8: Search Algorithms-Informed Search Lecture 42 Introduction to Informed Search Algorithms Lecture 43 Best First Search Lecture 44 Greedy Search Algorithm Lecture 45 A* Algorithm Section 9: Local Search Lecture 46 Introduction to Local Search Lecture 47 Hill Climbing Method Lecture 48 Variants of Hill Climbing Method Lecture 49 Applications of Hill Climbing Section 10: About the Program Lecture 50 Course Conclusion Anyone interested in the field of Artificial Intelligence,Students from Engineering HOMEPAGE DOWNLOAD |