machine learning artificial intelligence books collection

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machine learning artificial intelligence books collection

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种子哈希：34a485f6415e9b32200adabc7ef8ff84bb493fa5
文件大小：726.19M
已经下载：2886次
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收录时间：2024-02-02
最近下载：2025-08-12

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文件列表

  • Probabilistic Machine Learning: Advanced Topics [Kevin P. Murphy] - The MIT Press (2023).pdf 152.3 MB
  • Probabilistic Machine Learning: An Introduction [Kevin P. Murphy] - The MIT Press (2022).pdf 84.2 MB
  • Michael I. Jordan (Editor) - Learning in Graphical Models (Adaptive Computation and Machine Learning) (1998).pdf 59.6 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 38.9 MB
  • Stuart J. Russell, Peter Norvig - Artificial Intelligence_ A Modern Approach, Global Edition (2021, Pearson) - libgen.li.pdf 34.1 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 32.0 MB
  • Machine Learning: A Probabilistic Perspective [Kevin P. Murphy] - The MIT Press (2012).pdf 26.9 MB
  • Gilbert Strang - Linear Algebra and Learning from Data (2019, Wellesley-Cambridge Press).pdf 26.3 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 25.2 MB
  • Jonas Peters, Dominik Janzing, Bernhard Schölkopf - Elements of Causal Inference_ Foundations and Learning Algorithms-The MIT Press (2017).pdf 22.0 MB
  • Albert Bifet, Ricard Gavaldà, Geoff Holmes, Bernhard Pfahringer, Francis Bach - Machine Learning for Data Streams_ with Practical Examples in MOA.pdf 21.9 MB
  • An Introduction to Statistical Learning With Applications in Python [Robert Tibshirani,Jonathan Taylor] First Print July 2023.pdf 20.1 MB
  • Deep learning [Yoshua Bengio,Aaron Courville, Ian Goodfellow] - The MIT Press (2016) .pdf 19.3 MB
  • Pattern Recognition and Machine Learning [Christopher Bishop] (2006).pdf 18.1 MB
  • Freund, Yoav_Schapire, Robert E - Boosting foundations and algorithms-MIT Press (2012).pdf 16.3 MB
  • Elad Hazan - Introduction to Online Convex Optimization-The MIT Press (2022).epub 15.2 MB
  • Marc G. Bellemare - Distributional Reinforcement Learning - MIT Press (2023).epub 14.0 MB
  • Ethem Alpaydin - Introduction to Machine Learning (2020, The MIT Press) - libgen.li.pdf 13.5 MB
  • [Springer Series in Statistics] Trevor Hastie, Robert Tibshirani, Jerome Friedman - The Elements of Statistical Learning_ Data Mining, Inference, and Prediction. (2013, Springer).pdf 13.3 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 13.0 MB
  • Masashi Sugiyama, Motoaki Kawanabe - Machine Learning in Non-Stationary Environments_ Introduction to Covariate Shift Adaptation (2012, The MIT Press).pdf 12.7 MB
  • Daphne Koller, Nir Friedman - Probabilistic Graphical Models_ Principles and Techniques (2009, The MIT Press).pdf 8.9 MB
  • Mehryar Mohri_ Afshin Rostamizadeh_ Ameet Talwalkar - Foundations of Machine Learning (2018, The MIT Press).pdf 8.7 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 6.6 MB
  • Jacob Eisenstein - Introduction to Natural Language Processing (Instructor's Solution Manual) (2019, The MIT Press).7z 6.4 MB
  • David J. Hand, Heikki Mannila, Padhraic Smyth - Principles of data mining-MIT Press (2001).djvu 4.9 MB
  • Lise Getoor, Ben Taskar - Introduction to Statistical Relational Learning (2007).pdf 4.7 MB
  • Jacob Eisenstein - Natural Language Processing-MIT Press(2018).pdf 4.6 MB
  • Richard S. Sutton, Andrew G. Barto - Reinforcement learning_ an introduction (1998, The MIT Press).pdf 3.8 MB
  • Pierre Baldi, Soren Brunak - Bioinformatics_ the machine learning approach-The MIT Press (2001).pdf 3.4 MB
  • Peter Spirtes, Clark Glymour, Richard Scheines - Causation, Prediction, and Search, Second Edition (2001, The MIT Press).pdf 3.3 MB
  • Peter D. Grunwald, Jorma Rissanen - The minimum description length principle-MIT Press (2007).pdf 3.2 MB
  • Brendan J. Frey - Graphical Models for Machine Learning and Digital Communication (1998, The MIT Press) - libgen.li.pdf 2.9 MB
  • Ralf Herbrich - Learning Kernel Classifiers Theory and Algorithms (2001, The MIT Press).pdf 2.8 MB
  • Carl Edward Rasmussen, Christopher K. I. Williams - Gaussian Processes for Machine Learning (2006, MIT Press).pdf 2.8 MB
  • Machine Learning: A Probabilistic Perspective (Instructor's Solution Manual) [Kevin P. Murphy] - The MIT Press (2012).pdf 1.8 MB
  • Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar - Foundations of Machine Learning, Second Edition [2nd Ed] (Instructor Res. last of 3, Figure.7z 1.8 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 758.7 kB
  • Probabilistic Machine Learning: An Introduction [Kevin P. Murphy] (Instructor's Solution Manual) - The MIT Press (2022).pdf 629.4 kB
  • .pad/508647 508.6 kB
  • .pad/504823 504.8 kB
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  • .pad/322694 322.7 kB
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  • .pad/313881 313.9 kB
  • .pad/300086 300.1 kB
  • .pad/289898 289.9 kB
  • .pad/259305 259.3 kB
  • .pad/231055 231.1 kB
  • .pad/222608 222.6 kB
  • .pad/214484 214.5 kB
  • .pad/202714 202.7 kB
  • .pad/173109 173.1 kB
  • .pad/166693 166.7 kB
  • .pad/156588 156.6 kB
  • .pad/128700 128.7 kB
  • .pad/114626 114.6 kB
  • .pad/111887 111.9 kB
  • .pad/100077 100.1 kB
  • .pad/79712 79.7 kB
  • .pad/61159 61.2 kB
  • .pad/37040 37.0 kB
  • .pad/19770 19.8 kB
  • .pad/7200 7.2 kB

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