EbookFoundation
/
free-programming-books
mirror of https://github.com/EbookFoundation/free-programming-books.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Merge 267ec88e4d into 9bd33204fa

Dhiraj Kumar 2024-11-13 02:15:34 +00:00 committed by GitHub
parent 9bd33204fa 267ec88e4d
commit fbfdb7c803
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 3 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
books/free-programming-books-subjects.md
View File

@ -405,7 +405,7 @@ Books that cover a specific programming language can be found in the [BY PROGRAM
### Machine Learning
* [A Brief Introduction to Machine Learning for Engineers](https://arxiv.org/pdf/1709.02840.pdf) - Osvaldo Simeone (PDF)
* [A Brief Introduction to Neural Networks](https://www.dkriesel.com/en/science/neural_networks)
* [A Brief Introduction to Neural Networks](https://www.dkriesel.com/en/science/neural_networks) (CC BY-ND)
* [A Comprehensive Guide to Machine Learning](https://www.eecs189.org/static/resources/comprehensive-guide.pdf) - Soroush Nasiriany, Garrett Thomas, William Wang, Alex Yang (PDF)
* [A Course in Machine Learning](http://ciml.info/dl/v0_9/ciml-v0_9-all.pdf) (PDF)
* [A First Encounter with Machine Learning](https://web.archive.org/web/20210420163002/https://www.ics.uci.edu/~welling/teaching/ICS273Afall11/IntroMLBook.pdf) - Max Welling (PDF) *(:card_file_box: archived)*
@ -420,11 +420,11 @@ Books that cover a specific programming language can be found in the [BY PROGRAM
* [Dive into Deep Learning](https://d2l.ai)
* [Explorations in Parallel Distributed Processing: A Handbook of Models, Programs, and Exercises](https://web.stanford.edu/group/pdplab/pdphandbook) - James L. McClelland
* [Foundations of Machine Learning, Second Edition](https://mitpress.ublish.com/ebook/foundations-of-machine-learning--2-preview/7093/Cover) - Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar
* [Free and Open Machine Learning](https://nocomplexity.com/documents/fossml/) - Maikel Mardjan (HTML)
* [Free and Open Machine Learning](https://nocomplexity.com/documents/fossml/) - Maikel Mardjan (HTML) (CC BY-SA)
* [Gaussian Processes for Machine Learning](https://www.gaussianprocess.org/gpml/) - Carl Edward Rasmussen, Christopher K.I. Williams
* [IBM Machine Learning for Dummies](https://www.ibm.com/downloads/cas/GB8ZMQZ3) - Judith Hurwitz, Daniel Kirsch
* [Information Theory, Inference, and Learning Algorithms](http://www.inference.phy.cam.ac.uk/itila/) - David J.C. MacKay
* [Interpretable Machine Learning](https://christophm.github.io/interpretable-ml-book/) - Christoph Molnar
* [Interpretable Machine Learning](https://christophm.github.io/interpretable-ml-book/) (CC BY-NC-SA) - Christoph Molnar
* [Introduction to CNTK Succinctly](https://www.syncfusion.com/ebooks/cntk_succinctly) - James McCaffrey
* [Introduction to Machine Learning](https://arxiv.org/abs/0904.3664v1) - Amnon Shashua
* [Keras Succinctly](https://www.syncfusion.com/ebooks/keras-succinctly) - James McCaffrey