CS229: Machine Learning
Course Description This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs, practica
Top 8 Hands-On Books For ML Practitioners
Machine learning is a vast field. Thanks to the internet, there are plenty of resources available to get your hands on it — from books to blogs to vlogs. Analytics India Magazine has been compiling learning resources for the ML community for quite some time now. In this article, we list down top machine learning books for those who want to get practical with algorithms. (The books below are listed
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Netflix’s Polynote is a New Open Source Framework to Build Better Data Science Notebooks
The tidymodels Package
