Machine Learning

Explainable AI Machine Learning

New Book: Interpretable Machine Learning

Subtitled “A Guide for Making Black Box Models Explainable”. Authored and self-published by Christoph Molnar, 2022 (319 pages). This is actually the second edition, the first one was published in 2019. According to Google Scholar, it was cited more than 2,500 times. So this is a popular book about a popular topic. General Comments The […]

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Books Deep Learning Machine Learning

New Book: Efficient Deep Learning

Subtitled “Fast, smaller, and better models”. This book goes through algorithms and techniques used by researchers and engineers at Google Research, Facebook AI Research (FAIR), and other eminent AI labs to train and deploy their models on devices ranging from large server-side machines to tiny microcontrollers. The book presents a balance of fundamentals as well […]

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Data Sets Explainable AI Featured Posts Machine Learning ML with Excel Statistical Science Synthetic Data

Little Known Secrets about Interpretable Machine Learning on Synthetic Data

This first article in a new series on synthetic data and explainable AI, focuses on making linear regression more meaningful and controllable. Includes synthetic data, advanced machine learning with Excel, combinatorial feature selection, parametric bootstrap, cross-validation, and alternatives to R-squared to measure model performance. The full technical article (PDF, 13 pages, with detailed explanations and […]

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Books Machine Learning ML with Excel Visualization

Upcoming Books and Articles on

The future of machine learning and artificial intelligence. Here I share my roadmap for the next 12 months. While I am also looking for external contributors and authors to add more variety, my focus — as far as my technical content is concerned — is to complete the following projects and publish the material on this platform. All my blog posts will be available to everyone.

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Explainable AI Machine Learning ML with Excel Synthetic Data Visualization

Computer Vision: Shape Classification via Explainable AI

Update: The technical report on this topic is now available in the Resources section, here. Look for the title “Classification of Shapes via Explainable AI” under Free Books and Articles. A central problem in computer vision is to compare shapes and assess how similar they are. This is used for instance in text recognition. Modern […]

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Deep Learning Featured Posts Machine Learning

Amazing Neural Network Video Demonstration

I recently posted an article featuring a very deep neural network in action (250 layers), see here. Each frame in the video represented one layer, with the signal propagating from one layer to the next. In the last layer, the whole space was classified, in the sense that any new observation was immediately assigned to […]

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Deep Learning Machine Learning

New Neural Network with 500 Billion Parameters

Google just published a research article about its Pathways Language Model (PaML), a neural network with 500 billion parameters. It is unclear to me how many layers and how many neurons (also called nodes) it can handle. A parameter in this context is a weight attached to a link between two connected neurons. So the […]

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Machine Learning Statistical Science

Why are Confidence Regions Elliptic? Simple Explanation

A 90% confidence region is a domain of minimum area, containing 90% of the mass of a distribution. By distribution, here I mean a bivariate probability distribution, though the concept is not specific to machine learning. The 90% is called the confidence level, and I denote it as γ. Confidence regions are a generalization of […]

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Deep Learning Explainable AI Machine Learning Synthetic Data Visualization

Very Deep Neural Networks Explained in 40 Seconds

Very deep neural networks (VDNN) illustrated with data animation: a 40 second video, featuring supervised learning, layers, neurons, fuzzy classification, and convolution filters. It is said that a picture is worth a thousand words. Here instead, I use a video to illustrate the concept of very deep neural networks (VDNN). I use a supervised classification […]

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Books Explainable AI Featured Posts Machine Learning ML with Excel Statistical Science Stochastic Systems Synthetic Data Visualization

New Book: Stochastic Processes and Simulations

Introduction This scratch course on stochastic processes covers significantly more material than usually found in traditional books or classes. The approach is original: I introduce a new yet intuitive type of random structure called perturbed lattice or Poisson-binomial process, as the gateway to all the stochastic processes. Such models have started to gain considerable momentum […]

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