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Machine Learning with scikit-learn Part 2


This tutorial aims to provide an introduction to machine learning and scikit- learn "from the ground up". We will start with core concepts of machine learning, some example uses of machine learning, and how to implement them using scikit-learn. Going in detail through the characteristics of several methods, we will discuss how to pick an algorithm for your application, how to set its hyper-parameters, and how to evaluate performance. This is a two part tutorial. Please register for part one and part two. Prerequisite skills: NumPy, matplotlibPresenter(s): Speaker: Andreas Mueller, Columbia University Speaker: Guillaume Lemaitre, INRIA Saclay - Parietal team


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