- 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).
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.
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.
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.
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.
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.
Anand Rajaraman, Jeff Ullman, Jure Leskovec, Mining Massive Datasets, Stanford, Textbook
