**ARTIFICIAL INTELLIGENCE (AI), A TEXTBOOK** - Jul 27, 2021.

This book covers the broader field of AI, carefully balancing coverage between classical AI (logic or deductive reasoning) and modern AI (inductive learning and neural networks).

Tags: AI, Book, Charu Aggarwal, Textbook

**KDnuggets™ News 18:n34, Sep 12: Essential Math for Data Science; 100 Days of Machine Learning Code; Drop Dropout** - Sep 12, 2018.

Also: Neural Networks and Deep Learning: A Textbook; Don't Use Dropout in Convolutional Networks; Ultimate Guide to Getting Started with TensorFlow.

Tags: Deep Learning, Dropout, Machine Learning, Mathematics, Textbook

**Top /r/MachineLearning Posts, Apr 12-18: Andrew Ng AMA, Autoencoders, and Deep Learning Textbooks** - Apr 23, 2015.

Andrew Ng's AMA, a probabilistic view of Autoencoders, open source sentiment analysis, deep learning textbooks, and Airbnb's host matching are all discussed this week on /r/MachineLearning.

Tags: AirBnB, Andrew Ng, Baidu, Deep Learning, Grant Marshall, Open Source, Reddit, Sentiment Analysis, Textbook

**Companion Website for “Data Mining and Analysis: Fundamental Concepts and Algorithms”** - Nov 19, 2014.

Supplementary materials for the textbook Data Mining and Analysis: Fundamental Concepts and Algorithms are now available online and include figures, slides, datasets, videos, and more. Download them today.

Tags: Algorithms, Book, Data Mining, Mohammed Zaki, Textbook

**Book: Data Mining and Analysis: Fundamental Concepts and Algorithms** - May 27, 2014.

This textbook for senior undergraduate and graduate data mining courses provides a broad yet in-depth overview of data mining, integrating related concepts from machine learning and statistics. Companion website has data, slides and other teaching material.

Tags: Algorithms, Book, Data Mining, Mohammed Zaki, Textbook

**Book: Mining of Massive Datasets, 2nd Edition, free download** - Feb 12, 2014.

The second edition of this landmark book adds Jure Leskovec as a coauthor and has 3 new chapters, on mining large graphs, dimensionality reduction, and machine learning. You can still freely download a PDF version.

Tags: Anand Rajaraman, Jeff Ullman, Jure Leskovec, Mining Massive Datasets, Stanford, Textbook