Newsletter Sign-up and Resources

The following content (books, articles, spreadsheets, source code, data sets, tutorials) also includes material available to subscribers only. For the full book list, see here. For courses, see here. I will continue to add a lot more in the coming months.

Shape classification with explainable AI (see “Free books/articles” section)

Newsletter Subscription

To access subscriber-only content, sign-up to our free monthly newsletter at the bottom of this page. Newsletter subscription is free. You will receive an email with the password to access the material in question, listed on this page. This includes books, research articles, professional spreadsheets, original datasets, and more. You can unsubscribe at any time.

The monthly newsletter also features new blog posts, books, courses and other resources added to MLTechniques.com in the last 30 days, and occasionally, discount codes for selected books and articles available on our e-Store.


Blog Posts

Blog posts are available to everyone from our home page, here. You can browse them by category. Featured articles are available here.


Free Books and Articles For Subscribers Only

To open these PDF documents, use the password provided when signing-up or in any edition of our newsletter. The summary is accessible to everyone. When clicking on a “download” link, you get two options: view or download the file. The download option is much faster: the view option takes time to render all the fonts and pictures on the screen (up to 30 seconds for large documents). If you already have a copy of some of these documents, check out the version. The most recent version is posted here.

The LaTeX source is available to subscribers only, and contains the images, bibliography and the source code (in a zip file) used to produce the document. It allows you to easily copy and paste the Python code, change the style and formatting (such as font size) to your liking, or for easy inclusion in other documents. To access it, click on “Full version”. All the Python code is also on GitHub.

Technical Articles

  1. Math-free, Parameter-free Gradient Descent in Python
    Download PDF | Read summary | Full version. 14 pages, version 1.0. January 2023.
  2. New Interpolation Method for Data Synthetization and Prediction
    Download PDF | Read summary | Full version. 18 pages, version 2.0. January 2023.
  3. Military-grade Fast Random Number Generator Based on Quadratic Irrationals
    Download PDF | Read summary. 5 pages, version 1.0. December 2022. Not password-protected.
  4. Empirical Optimization with Divergent Fixed Point Algorithm – When All Else Fails
    Download PDF | Read summary. 12 pages, version 2.0. December 2022. Not password-protected.
  5. Spectacular Videos: Synthetic Universes, with Star Collision Graph
    Download PDF | Read summary | Full version. 13 pages, version 1.0. November 2022.
  6. Dynamic Clouds and Landscape Generation: Morphing and Evolutionary Processes
    Download PDF | Read summary | Full version. 9 pages, version 1.0. November 2022.
  7. Advanced Machine Learning with Basic Excel — Simple Alternative to XGBoost.
    Download PDF | Read summary | Full version. 10 pages, version 1.0. September 2022.
  8. Machine Learning Cloud Regression: The Swiss Army Knife of Optimization.
    Download PDF | Read summary | Full version. 25 pages, version 1.0. August 2022.
  9. Weird Random Walks: Synthetizing, Testing and Leveraging Quasi-randomness.
    Download PDF | Read summary | Full version. 10 pages, version 1.0. August 2022.
  10. Detecting Subtle Departures from Randomness.
    Download PDF | Read summary | Full version. 14 pages, version 1.1. July 2022.
  11. Classification and Clustering via Image Convolution Filters — Alternative to Generative Mixture Models.
    Download PDF | Read summary | Full version. 15 pages, version 1.0. June 2022.
  12. The Art of Visualizing High Dimensional Data.
    Download PDF | Read summary | Full version. 17 pages [22.8 MB], version 2.0. June 2022.
  13. Gentle Introduction to Linear Algebra, with Spectacular Applications.
    Download PDF | Read summary | Full version. 9 pages, version 2.2. June 2022.
  14. Interpretable Machine Learning: Multipurpose, Model-free, Math-free Fuzzy Regression.
    Download PDF | Read summary | Full version. 11 pages, version 1.1. May 2022.
  15. Classification of Shapes via Explainable AI.
    Download PDF | Read summary | Full version. 7 pages, version 1.0. April 2022.
  16. Interpretable Machine Learning on Synthetic Data, and Little Known Secrets About Linear Regression.
    Download PDF | Read summary | Full version. 13 pages, version 1.0. May 2022.
  17. New Perspective on the Riemann Hypothesis.
    Download PDF | Read summary | Full version. 23 pages, version 1.1. July 2022.

Books

  1. Statistics: New Foundations, Toolbox, and Machine Learning Recipes.
    Read summary | Download PDF. July 2019, 309 pages.
  2. Applied Stochastic Processes, Chaos Modeling, and Probabilistic Properties of Numeration Systems.
    Read summary | Download PDF. June 2018, 104 pages.


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