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Fix broken links in free programming books subjects (#7798)

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* Point chain.courses to The Web Archive

* Point Glib/GTK+ book to new official location

* Point Deep Learning with PyTorch to official HTML location

* Foundations of Machine Learning is still available through MIT Press preview site

* Point Introduction to Probability to new site

* LLNL tutorials have a new location

* Delete Deep Learning with PyTorch
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@ -144,7 +144,7 @@ Books that cover a specific programming language can be found in the [BY PROGRA
* [Bitcoin and Cryptocurrency Technologies](http://bitcoinbook.cs.princeton.edu) - Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller, Steven Goldfeder, Jeremy Clark (PDF)
* [Blockchain for Dummies, 2nd IBM Limited Edition](https://www.ibm.com/downloads/cas/36KBMBOG) - Manav Gupta (PDF)
* [chain.courses](https://chain.courses) - James Gan, Rishub Kumar
* [chain.courses](https://web.archive.org/web/20220127020549/https://chain.courses/) - James Gan, Rishub Kumar
* [Getting Started with Enterprise Blockchain: A Guide to Design and Development](https://www.ibm.com/downloads/cas/RYWXAR0M) - Michael Bradley, David Gorman, Matt Lucas, Matthew Golby-Kirk (PDF)
* [Grokking Bitcoin](https://rosenbaum.se/book/) - Kalle Rosenbaum (HTML)
* [IBM Blockchain: The Founder’s Handbook, Third Edition](https://www.ibm.com/downloads/cas/GZPPMWM5) - Antonio Banda, Matthew Hamilton, Eileen Lowry, John Widdifield, et al. (PDF)
@ -363,10 +363,9 @@ Books that cover a specific programming language can be found in the [BY PROGRA
* [Bayesian Reasoning and Machine Learning](http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.HomePage)
* [Deep Learning](http://www.deeplearningbook.org) - Ian Goodfellow, Yoshua Bengio, Aaron Courville
* [Deep Learning for Coders with Fastai and PyTorch](https://github.com/fastai/fastbook) - Jeremy Howard, Sylvain Gugger (Jupyter Notebooks)
* [Deep Learning with PyTorch](https://pytorch.org/assets/deep-learning/Deep-Learning-with-PyTorch.pdf) - Eli Stevens, Luca Antiga, Thomas Viehmann (PDF)
* [Dive into Deep Learning](http://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/ereader/7093/?preview=#page/Cover) - Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar
* [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)
* [Gaussian Processes for Machine Learning](http://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
@ -675,7 +674,7 @@ Books that cover a specific programming language can be found in the [BY PROGRA
### Parallel Programming
* [High Performance Computing](http://cnx.org/contents/bb821554-7f76-44b1-89e7-8a2a759d1347%405.2) - Charles Severance, Kevin Dowd (PDF, ePUB)
* [High Performance Computing Training](https://web.archive.org/web/20170702124132/https://hpc.llnl.gov/training/tutorials) (LLNL materials)
* [High Performance Computing Training](https://hpc.llnl.gov/documentation/tutorials) (LLNL materials)
* [High-Performance Scientific Computing](https://andreask.cs.illinois.edu/Teaching/HPCFall2012) (class lectures and slides)
* [Introduction to High-Performance Scientific Computing](http://pages.tacc.utexas.edu/~eijkhout/istc/istc.html) - Victor Eijkhout
* [Introduction to Parallel Computing](https://hpc.llnl.gov/documentation/tutorials/introduction-parallel-computing-tutorial) - Blaise Barney