Info Hash:34A485F6415E9B32200ADABC7EF8FF84BB493FA5
收录时间2025-12-20 23:00:42
更新时间2025-12-20 23:22:18
文件列表 (77)
Albert Bifet, Ricard Gavaldà, Geoff Holmes, Bernhard Pfahringer, Francis Bach - Machine Learning for Data Streams_ with Practical Examples in MOA.pdf
20.89 MB
.pad/111887
109.26 KB
An Introduction to Statistical Learning With Applications in Python [Robert Tibshirani,Jonathan Taylor] First Print July 2023.pdf
19.16 MB
.pad/355244
346.92 KB
Brendan J. Frey - Graphical Models for Machine Learning and Digital Communication (1998, The MIT Press) - libgen.li.pdf
2.78 MB
.pad/231055
225.64 KB
Carl Edward Rasmussen, Christopher K. I. Williams - Gaussian Processes for Machine Learning (2006, MIT Press).pdf
2.68 MB
.pad/330311
322.57 KB
Daphne Koller, Nir Friedman - Probabilistic Graphical Models_ Principles and Techniques (2009, The MIT Press).pdf
8.44 MB
.pad/61159
59.73 KB
David J. Hand, Heikki Mannila, Padhraic Smyth - Principles of data mining-MIT Press (2001).djvu
4.63 MB
.pad/391027
381.86 KB
Deep learning [Yoshua Bengio,Aaron Courville, Ian Goodfellow] - The MIT Press (2016) .pdf
18.39 MB
.pad/114626
111.94 KB
Elad Hazan - Introduction to Online Convex Optimization-The MIT Press (2022).epub
14.49 MB
.pad/7200
7.03 KB
Ethem Alpaydin - Introduction to Machine Learning (2020, The MIT Press) - libgen.li.pdf
12.9 MB
.pad/100077
97.73 KB
Freund, Yoav_Schapire, Robert E - Boosting foundations and algorithms-MIT Press (2012).pdf
15.54 MB
.pad/486522
475.12 KB
Gilbert Strang - Linear Algebra and Learning from Data (2019, Wellesley-Cambridge Press).pdf
25.05 MB
.pad/467712
456.75 KB
Jacob Eisenstein - Introduction to Natural Language Processing (Instructor's Solution Manual) (2019, The MIT Press).7z
6.07 MB
.pad/454173
443.53 KB
Jacob Eisenstein - Natural Language Processing-MIT Press(2018).pdf
4.38 MB
.pad/128700
125.68 KB
Jonas Peters, Dominik Janzing, Bernhard Schölkopf - Elements of Causal Inference_ Foundations and Learning Algorithms-The MIT Press (2017).pdf
20.96 MB
.pad/37040
36.17 KB
Lise Getoor, Ben Taskar - Introduction to Statistical Relational Learning (2007).pdf
4.52 MB
.pad/504823
492.99 KB
Machine Learning: A Probabilistic Perspective (Instructor's Solution Manual) [Kevin P. Murphy] - The MIT Press (2012).pdf
1.7 MB
.pad/313881
306.52 KB
Machine Learning: A Probabilistic Perspective [Kevin P. Murphy] - The MIT Press (2012).pdf
25.69 MB
.pad/320307
312.8 KB
Marc G. Bellemare - Distributional Reinforcement Learning - MIT Press (2023).epub
13.35 MB
.pad/156588
152.92 KB
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
37.05 MB
.pad/471467
460.42 KB
Masashi Sugiyama, Motoaki Kawanabe - Machine Learning in Non-Stationary Environments_ Introduction to Covariate Shift Adaptation (2012, The MIT Press).pdf
12.1 MB
.pad/418917
409.1 KB
Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar - Foundations of Machine Learning, Second Edition [2nd Ed] (Instructor Res. last of 3, Figure.7z
1.69 MB
.pad/322694
315.13 KB
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
.pad/289898
283.1 KB
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
24.06 MB
.pad/457293
446.58 KB
Mehryar Mohri_ Afshin Rostamizadeh_ Ameet Talwalkar - Foundations of Machine Learning (2018, The MIT Press).pdf
8.3 MB
.pad/214484
209.46 KB
Michael I. Jordan (Editor) - Learning in Graphical Models (Adaptive Computation and Machine Learning) (1998).pdf
56.83 MB
.pad/173109
169.05 KB
Pattern Recognition and Machine Learning [Christopher Bishop] (2006).pdf
17.25 MB
.pad/259305
253.23 KB
Peter D. Grunwald, Jorma Rissanen - The minimum description length principle-MIT Press (2007).pdf
3.01 MB
.pad/508647
496.73 KB
Peter Spirtes, Clark Glymour, Richard Scheines - Causation, Prediction, and Search, Second Edition (2001, The MIT Press).pdf
3.11 MB
.pad/410859
401.23 KB
Pierre Baldi, Soren Brunak - Bioinformatics_ the machine learning approach-The MIT Press (2001).pdf
3.29 MB
.pad/222608
217.39 KB
Probabilistic Machine Learning: Advanced Topics [Kevin P. Murphy] - The MIT Press (2023).pdf
145.21 MB
.pad/300086
293.05 KB
Probabilistic Machine Learning: An Introduction [Kevin P. Murphy] (Instructor's Solution Manual) - The MIT Press (2022).pdf
614.66 KB
.pad/419167
409.34 KB
Probabilistic Machine Learning: An Introduction [Kevin P. Murphy] - The MIT Press (2022).pdf
80.34 MB
.pad/166693
162.79 KB
Ralf Herbrich - Learning Kernel Classifiers Theory and Algorithms (2001, The MIT Press).pdf
2.69 MB
.pad/324801
317.19 KB
Richard S. Sutton, Andrew G. Barto - Reinforcement learning_ an introduction (1998, The MIT Press).pdf
3.59 MB
.pad/430110
420.03 KB
Stuart J. Russell, Peter Norvig - Artificial Intelligence_ A Modern Approach, Global Edition (2021, Pearson) - libgen.li.pdf
32.54 MB
.pad/482628
471.32 KB
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
12.42 MB
.pad/79712
77.84 KB
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
30.48 MB
.pad/19770
19.31 KB
[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
6.31 MB
.pad/202714
197.96 KB
[Springer Series in Statistics] Trevor Hastie, Robert Tibshirani, Jerome Friedman - The Elements of Statistical Learning_ Data Mining, Inference, and Prediction. (2013, Springer).pdf