machine learning artificial intelligence books collection
File List
- Probabilistic Machine Learning: Advanced Topics [Kevin P. Murphy] - The MIT Press (2023).pdf 145.2 MB
- Probabilistic Machine Learning: An Introduction [Kevin P. Murphy] - The MIT Press (2022).pdf 80.3 MB
- Michael I. Jordan (Editor) - Learning in Graphical Models (Adaptive Computation and Machine Learning) (1998).pdf 56.8 MB
- Masashi Sugiyama, Han Bao, Takashi Ishida, Nan Lu, Tomoya Sakai - Machine Learning from Weak Supervision_ An Empirical Risk Minimization Approach (2022, The MIT Press) - li.pdf 37.1 MB
- Stuart J. Russell, Peter Norvig - Artificial Intelligence_ A Modern Approach, Global Edition (2021, Pearson) - libgen.li.pdf 32.5 MB
- Stuart Russell, Peter Norvig - Artificial Intelligence_ A Modern Approach, Fourth Global Edition [4th Ed] (Instructor Res. n. last of 2, Lectures) (2021, Pearson Education Limited) - libgen.li.7z 30.5 MB
- Machine Learning: A Probabilistic Perspective [Kevin P. Murphy] - The MIT Press (2012).pdf 25.7 MB
- Gilbert Strang - Linear Algebra and Learning from Data (2019, Wellesley-Cambridge Press).pdf 25.1 MB
- Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar - Foundations of Machine Learning, Second Edition [2nd Ed] (Instructor Res. n. 2 of 3, Lectures) (2018, The MIT Press) - .7z 24.1 MB
- Jonas Peters, Dominik Janzing, Bernhard Schölkopf - Elements of Causal Inference_ Foundations and Learning Algorithms-The MIT Press (2017).pdf 21.0 MB
- Albert Bifet, Ricard Gavaldà, Geoff Holmes, Bernhard Pfahringer, Francis Bach - Machine Learning for Data Streams_ with Practical Examples in MOA.pdf 20.9 MB
- An Introduction to Statistical Learning With Applications in Python [Robert Tibshirani,Jonathan Taylor] First Print July 2023.pdf 19.2 MB
- Deep learning [Yoshua Bengio,Aaron Courville, Ian Goodfellow] - The MIT Press (2016) .pdf 18.4 MB
- Pattern Recognition and Machine Learning [Christopher Bishop] (2006).pdf 17.3 MB
- Freund, Yoav_Schapire, Robert E - Boosting foundations and algorithms-MIT Press (2012).pdf 15.5 MB
- Elad Hazan - Introduction to Online Convex Optimization-The MIT Press (2022).epub 14.5 MB
- Marc G. Bellemare - Distributional Reinforcement Learning - MIT Press (2023).epub 13.4 MB
- Ethem Alpaydin - Introduction to Machine Learning (2020, The MIT Press) - libgen.li.pdf 12.9 MB
- [Springer Series in Statistics] Trevor Hastie, Robert Tibshirani, Jerome Friedman - The Elements of Statistical Learning_ Data Mining, Inference, and Prediction. (2013, Springer).pdf 12.7 MB
- Stuart Russell, Peter Norvig - Artificial Intelligence_ A Modern Approach, Fourth Global Edition [4th Ed] (Instructor Res. n. 1 of 2, Solution Manual, Solutions)-Pearson Education Limited (2021).7z 12.4 MB
- Masashi Sugiyama, Motoaki Kawanabe - Machine Learning in Non-Stationary Environments_ Introduction to Covariate Shift Adaptation (2012, The MIT Press).pdf 12.1 MB
- Daphne Koller, Nir Friedman - Probabilistic Graphical Models_ Principles and Techniques (2009, The MIT Press).pdf 8.4 MB
- Mehryar Mohri_ Afshin Rostamizadeh_ Ameet Talwalkar - Foundations of Machine Learning (2018, The MIT Press).pdf 8.3 MB
- [Morgan Kaufmann Series in Data Management Systems] Ian H. Witten, Eibe Frank, Mark A. Hall, Christopher J. Pal - Data Mining_ Practical Machine Learning Tools and Techniques (2016, Morgan Kaufmann Publishers).pdf 6.3 MB
- Jacob Eisenstein - Introduction to Natural Language Processing (Instructor's Solution Manual) (2019, The MIT Press).7z 6.1 MB
- David J. Hand, Heikki Mannila, Padhraic Smyth - Principles of data mining-MIT Press (2001).djvu 4.6 MB
- Lise Getoor, Ben Taskar - Introduction to Statistical Relational Learning (2007).pdf 4.5 MB
- Jacob Eisenstein - Natural Language Processing-MIT Press(2018).pdf 4.4 MB
- Richard S. Sutton, Andrew G. Barto - Reinforcement learning_ an introduction (1998, The MIT Press).pdf 3.6 MB
- Pierre Baldi, Soren Brunak - Bioinformatics_ the machine learning approach-The MIT Press (2001).pdf 3.3 MB
- Peter Spirtes, Clark Glymour, Richard Scheines - Causation, Prediction, and Search, Second Edition (2001, The MIT Press).pdf 3.1 MB
- Peter D. Grunwald, Jorma Rissanen - The minimum description length principle-MIT Press (2007).pdf 3.0 MB
- Brendan J. Frey - Graphical Models for Machine Learning and Digital Communication (1998, The MIT Press) - libgen.li.pdf 2.8 MB
- Ralf Herbrich - Learning Kernel Classifiers Theory and Algorithms (2001, The MIT Press).pdf 2.7 MB
- Carl Edward Rasmussen, Christopher K. I. Williams - Gaussian Processes for Machine Learning (2006, MIT Press).pdf 2.7 MB
- Machine Learning: A Probabilistic Perspective (Instructor's Solution Manual) [Kevin P. Murphy] - The MIT Press (2012).pdf 1.7 MB
- Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar - Foundations of Machine Learning, Second Edition [2nd Ed] (Instructor Res. last of 3, Figure.7z 1.7 MB
- Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar - Foundations of Machine Learning, Second Edition [2nd Ed] (Instructor Res. n. 1 of 3, Solution Manual, Solutions) (2018.pdf 740.9 KB
- Probabilistic Machine Learning: An Introduction [Kevin P. Murphy] (Instructor's Solution Manual) - The MIT Press (2022).pdf 614.7 KB
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