Getting Started with Artificial Intelligence , 2nd Edition
25Technical TutorialsData ScienceMachine Learning
Comprehensive introduction to AI, covering machine learning and data science. Practical guide to building enterprise applications with real-world examples.
Machine Learning For Dummies, IBM Limited Edition
19Technical TutorialsData ScienceMachine Learning
Comprehensive guide to machine learning and data science, suitable for beginners and experienced professionals. Authored by experts Daniel Kirsch and Judith Hurwitz.
Data Mining Concepts and Techniques
25Technical TutorialsData ScienceMachine Learning
Comprehensive coverage of data mining concepts and techniques, including data preprocessing, classification, clustering, and association rule mining. Essential resource for students, researchers, and professionals in data mining, machine learning, and data analysis.
Probability and Statistics with Examples using R
3Technical TutorialsR
Comprehensive guide to probability and statistics using R, with emphasis on mathematical rigor, real-world examples, and computational tools.
A Brief Introduction to Machine Learning for Engineers
29Technical TutorialsMachine Learning
Gain a solid understanding of machine learning concepts and techniques for engineers. Covers supervised, unsupervised, probabilistic models, and advanced topics.
A Comprehensive Guide to Machine Learning
24Technical TutorialsData ScienceMachine Learning
Detailed resource on machine learning, data science, and artificial intelligence. Authored by experienced experts, suitable for beginners and experienced learners.
A First Encounter with Machine Learning
2Technical TutorialsData ScienceMachine Learning
Explore fundamental machine learning concepts, algorithms, and applications in data science. Suitable for beginners interested in learning about this rapidly growing field.
A Selective Overview of Deep Learning
3Technical TutorialsDeep LearningMachine LearningNeural Networks
Comprehensive overview of key concepts and recent advancements in deep learning, covering neural network models, training techniques, and theoretical foundations.
Algorithms for Reinforcement Learning
6Technical TutorialsMachine LearningReinforcement Learning
Comprehensive guide to reinforcement learning algorithms, covering dynamic programming, temporal difference, Monte-Carlo methods, and more. Suitable for researchers, students, and practitioners in AI, ML, and control engineering.