Upcoming Books and Articles on MLTechniques.com
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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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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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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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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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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