Notion Press, 2023. — 388 p. — eISBN: 979-8-89026-836-5.
How does our brain work in our routine life? The same way we design artificial intelligence in machines. Instead of complex straightforward theory, this book explains all logic and algorithms with the help of day-to-day examples. The language is straightforward. Besides, the examples are straightforward. We adequately cover all functions of the intelligent agent and machine learning models. This book is a sweet friend for newcomers to the AI field (this includes academic students and working professionals.). This book additionally includes statistical models. The overall intention of this book is to spread the knowledge to all kinds of readers preparing themselves to secure a visa for the upcoming AI-driven earth.
Introduction to Artificial Intelligence and Machine Learning.
Part 1. Artificial IntelligenceArtificial Intelligence: Introduction.
Artificial Intelligence: Search and Problem-Solving.
Artificial Intelligence: Local Search.
Artificial Intelligence: Adversarial Search Games.
Artificial Intelligence: Logic and logical agents.
Artificial Intelligence: Uncertainty.
Artificial Intelligence: Top View Agent and Environments.
Artificial Intelligence: Ethics.
Cyber Security with AI and ML Systems.
Part 2. Statistical MethodsStatistical Methods: Statistics and Probability Basics.
Statistical Methods: Independent probability.
Statistical Methods: Discrete Random Variables.
Statistical Methods: Sampling.
Statistical Methods: Hypothesis Testing.
Machine Learning: Introduction.
Machine Learning: Data Workflow and Data Mining.
Machine Learning: Linear Regression Models.
Machine Learning: Classification (Linear and Logistic classification).
Machine Learning: Decision Tree.
Machine Learning: Instance-based Learning Algorithms.
Machine Learning: Support Vector Machine.
Machine Learning: Bayesian Learning.
Machine Learning: Ensemble Learning.
Machine Learning: Unsupervised Learning.