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Tag: “Statistical Mechanics Neural Networks and Machine Learning” (THE Book)

“Statistical Mechanics, Neural Networks, and Machine Learning” (THE Book) is a book-in-progress by Dr. A.J. Maren, on precisely those topics. It is designed for people who are learning machine learning – and who NEED TO LEARN statistical mechanics – and gives the simplest-possible, most pain-free, and easy to understand and assimilate guide.

Book Chapter: Draft Chapter 7 – The Boltzmann Machine

Book Chapter: Draft Chapter 7 – The Boltzmann Machine

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Chapter 7: Energy-Based Neural Networks This is the full chapter draft from the book-in-progress, Statistical Mechanics, Neural Networks, and Artificial Intelligence. This chapter draft covers not only the Hopfield neural network (released as an excerpt last week), but also the Boltzmann machine, in both general and restricted forms. It deals with that form-equals-function connection, based on the energy equation. (However, we postpone the full-fledged learning method to a later chapter.) Get the pdf using the pdf link in the citation…

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Notational Frenzy

Notational Frenzy

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When the Subtle Art of Mathematical Notation Defeats You (and How to Fight Back)   A couple of years ago, I was teaching Time Series and Forecasting for the first time. I didn’t know the subject – at all – but that didn’t bother me. Hey, it was mathematics, right? Anything that’s mathematical, I can eat for lunch, and then want some dessert-equations afterwards. First week, introducing the subject. That went fine. Second week, Simple Exponential Smoothing (SES). That’s simple….

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Seven Essential Machine Learning Equations: A Cribsheet (Really, the Précis)

Seven Essential Machine Learning Equations: A Cribsheet (Really, the Précis)

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Making Machine Learning As Simple As Possible Albert Einstein is credited with saying, Everything should be made as simple as possible, but not simpler. Machine learning is not simple. In fact, once you get beyond the simple “building blocks” approach of stacking things higher and deeper (sometimes made all too easy with advanced deep learning packages), you are in the midst of some complex stuff. However, it does not need to be more complex than it has to be.  …

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A Tale of Two Probabilities

A Tale of Two Probabilities

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Probabilities: Statistical Mechanics and Bayesian:   Machine learning fuses several different lines of thought, including statistical mechanics, Bayesian probability theory, and neural networks. There are two different ways of thinking about probability in machine learning; one comes from statistical mechanics, and the other from Bayesian logic. Both are important. They are also very different. While these two different ways of thinking about probability are usually very separate, they come together in some of the more advanced machine learning topics, such…

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The Statistical Mechanics Underpinnings of Machine Learning

The Statistical Mechanics Underpinnings of Machine Learning

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Machine Learning Is Different Now:   Actually, machine learning is a continuation of what it always has been, which is deeply rooted in statistical physics (statistical mechanics). It’s just that there’s a culmination of insights that are now a very substantive body of work, with more theoretical rigor behind them than most of us know.     A Lesson from Mom: It takes a lot of time to learn a new discipline. This is something that I learned from my…

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Seven Statistical Mechanics / Bayesian Equations That You Need to Know

Seven Statistical Mechanics / Bayesian Equations That You Need to Know

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Essential Statistical Mechanics for Deep Learning   If you’re self-studying machine learning, and feel that statistical mechanics is suddenly showing up more than it used to, you’re not alone. Within the past couple of years, statistical mechanics (statistical thermodynamics) has become a more integral topic, along with the Kullback-Leibler divergence measure and several inference methods for machine learning, including the expectation maximization (EM) algorithm along with variational Bayes.     Statistical mechanics has always played a strong role in machine…

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