Adding Free Python, Datamining, Machine Learning Books (Correct Categories) (#4882)

* Adding Free Python, Datamining, Machine Learning Books (Corrected Categories)

There were a few issues with my original PR (https://github.com/EbookFoundation/free-programming-books/pull/4866/files), so I forked the main respository and added my updates based on @eshellman 's feedback.

Edits include:
- moving "Top 10 Machine Learning Algos..." by Mathews and Aasim --> Machine Learning
- moving "A Select Overview of Deep Learning" by Fan, Ma, and Zhong --> Machine Learning
- adding "Natural Langauge NLP with Python Tutorial" --> Python
- moving "The Ultimate Guide to 12 Dimensionality Reduction Techniques" by Sharma --> Datamining

Note: there was a linter error coming up in the previous PR that I wasn't sure about (https://github.com/EbookFoundation/free-programming-books/pull/4866)....so hopefully this is all set!

* Update free-programming-books.md

Fixed the four errors coming up in TravisCI (adding extra line, and also some alphabetizing). Should be good to go now!

    445:1-455:191  warning  Incorrect number of blank lines between last section and next heading  blank-lines-1-0-2

    445:1-455:191  warning  Alphabetical ordering: swap l.455 and l.454                            alphabetize-lists

    472:1-509:163  warning  Alphabetical ordering: swap l.506 and l.505                            alphabetize-lists

  2315:1-2408:101  warning  Alphabetical ordering: swap l.2362 and l.2361                          alphabetize-lists

free-programming-books.md

@@ -451,6 +451,7 @@
 * [Mining of Massive Datasets](http://www.mmds.org)
 * [School of Data Handbook](http://schoolofdata.org/handbook/)
 * [Statistical inference for data science](https://leanpub.com/LittleInferenceBook/read) - Brian Caffo
+* [The Ultimate Guide to 12 Dimensionality Reduction Techniques (with Python codes)](https://www.analyticsvidhya.com/blog/2018/08/dimensionality-reduction-techniques-python/) - Pulkit Sharma
 * [Theory and Applications for Advanced Text Mining](http://www.intechopen.com/books/theory-and-applications-for-advanced-text-mining)
 
 
@@ -474,6 +475,7 @@
 * [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://www.ics.uci.edu/~welling/teaching/ICS273Afall11/IntroMLBook.pdf) (PDF)
+* [A Selective Overview of Deep Learning](https://arxiv.org/abs/1904.05526) - Fan, Ma, and Zhong (PDF)
 * [Algorithms for Reinforcement Learning](https://sites.ualberta.ca/~szepesva/papers/RLAlgsInMDPs.pdf) - Csaba Szepesvári (PDF)
 * [An Introduction to Statistical Learning](http://www-bcf.usc.edu/~gareth/ISL/) - Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani
 * [Bayesian Reasoning and Machine Learning](http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.HomePage)
@@ -504,6 +506,7 @@
 * [The Elements of Statistical Learning](https://web.stanford.edu/~hastie/ElemStatLearn/) - Trevor Hastie, Robert Tibshirani, and Jerome Friedman
 * [The LION Way: Machine Learning plus Intelligent Optimization](https://intelligent-optimization.org/LIONbook/lionbook_3v0.pdf) - Roberto Battiti, Mauro Brunato (PDF)
 * [The Python Game Book](http://thepythongamebook.com/en%3Astart)
+* [Top 10 Machine Learning Algorithms Every Engineer Should Know](https://www.dezyre.com/article/top-10-machine-learning-algorithms/202) - Binny Mathews and Omair Aasim
 * [Understanding Machine Learning: From Theory to Algorithms](https://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning) - Shai Shalev-Shwartz, Shai Ben-David
 
 
@@ -2357,6 +2360,7 @@ Kerridge (PDF) (email address *requested*, not required)
 * [Math for programmers (using python)](https://akuli.github.io/math-tutorial/)
 * [Modeling and Simulation in Python](https://greenteapress.com/wp/modsimpy/) - Allen B. Downey (PDF)
 * [Modeling Creativity: Case Studies in Python](http://www.clips.ua.ac.be/sites/default/files/modeling-creativity.pdf) - Tom D. De Smedt (PDF)
+* [Natural Language Processing (NLP) with Python — Tutorial](https://medium.com/towards-artificial-intelligence/natural-language-processing-nlp-with-python-tutorial-for-beginners-1f54e610a1a0) (PDF)
 * [Natural Language Processing with Python](http://www.nltk.org/book/) (3.x)
 * [Non-Programmer's Tutorial for Python 3](https://en.wikibooks.org/wiki/Non-Programmer%27s_Tutorial_for_Python_3) - Wikibooks (3.3)
   * [Non-Programmer's Tutorial for Python 2.6](https://en.wikibooks.org/wiki/Non-Programmer%27s_Tutorial_for_Python_2.6) - Wikibooks (2.6)