Artificial intelligence and machine learning fundamentals develop real-world applications powered by the latest AI advances - Nagy, Zsolt (Packt, 2018)
Intro -- Preface -- Principles of Artificial Intelligence -- Introduction -- How does AI Solve Real World Problems? -- Diversity of Disciplines -- Fields and Applications of Artificial Intelligence -- Simulating Intelligence - The Turing Test -- AI Tools and Learning Models -- Classification and Prediction -- Learning Models -- The Role of Python in Artificial Intelligence -- Why is Python Dominant in Machine Learning, Data Science, and AI? -- Anaconda in Python -- Python Libraries for Artificial Intelligence -- A Brief Introduction to the NumPy Library -- Exercise 1: Matrix Operations Using NumPy -- Python for Game AI -- Intelligent Agents in Games -- Breadth First Search and Depth First Search -- Exploring the State Space of a Game -- Exercise 2: Estimating the Number of Possible States in Tic-Tac-Toe Game -- Exercise 3: Creating an AI Randomly -- Activity 1: Generating All Possible Sequences of Steps in a Tic-Tac-Toe Game -- Summary -- AI with Search Techniques and Games -- Introduction -- Exercise 4: Teaching the Agent to Win -- Activity 2: Teaching the Agent to Realize Situations When It Defends Against Losses -- Activity 3: Fixing the First and Second Moves of the AI to Make it Invincible -- Heuristics -- Uninformed and Informed Search -- Creating Heuristics -- Admissible and Non-Admissible Heuristics -- Heuristic Evaluation -- Exercise 5: Tic-Tac-Toe Static Evaluation with a Heuristic Function -- Using Heuristics for an Informed Search -- Types of Heuristics -- Pathfinding with the A* Algorithm -- Exercise 6: Finding the Shortest Path to Reach a Goal -- Exercise 7: Finding the Shortest Path Using BFS -- Introducing the A* Algorithm -- A* Search in Practice Using the simpleai Library -- Game AI with the Minmax Algorithm and Alpha-Beta Pruning -- Search Algorithms for Turn-Based Multiplayer Games -- The Minmax Algorithm
Keywords: Künstliche Intelligenz; Maschinelles Lernen