explained.ai
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About
explained.ai offers deep explanations of machine learning and related topics through articles, libraries, and videos. It provides resources for understanding complex topics such as RNNs, regularization, decision trees, gradient boosting, and matrix calculus. The site also features Python libraries for visualizing data structures and decision trees, along with academic papers on feature impact and partial dependence. The content is created by Terence Parr, a tech lead at Google and former professor of data science.
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Task
Features
• academic papers on feature impact and importance, partial dependence, and code formatting
• videos on deep learning and decision trees
• automatic differentiation library (autodx)
• python libraries for decision tree visualization (dtreeviz), random forest importances (rfpimp), and data-structure visualization (lolviz)
• articles on deep learning, rnns, regularization, decision trees, gradient boosting, and matrix calculus
• deep explanations of machine learning topics
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