Saturday Morning Videos: Andreas C. Müller's COMS W4995 Applied Machine Learning, Columbia/NYU CDS, Spring 2019

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Andreas is a contributor of Scikit-learn and just posted the videos of his course at the Institute for Data Science at NYU and Columbia. 

1:16:53

Applied Machine Learning 2019 - Lecture 19 - Word embeddings

1:18:24

Applied Machine Learning 2019 - Lecture 18 - Topic Models

1:16:45

Applied Machine Learning 2019 - Lecture 17 - Introduction to text data

1:04:24

Applied Machine Learning 2019 - Lecture 16 - NMF; Outlier detection

1:09:32

Applied Machine Learning 2019 - Lecture 15 - Clustering and Mixture models

1:15:24

Applied Machine Learning 2019 - Lecture 14 - Dimensionality Reduction

1:22:07

Applied Machine Learning 2019 - Lecture 13 - Parameter Selection and Automatic Machine Learning

1:17:05

Applied Machine Learning 2019 - Lecture 12 - Model Interpretration and Feature Selection

1:03:48

Applied Machine Learning 2019 - Lecture 11 - Imbalanced data

1:15:23

Applied Machine Learning 2019 - Lecture 10 - Model Evaluation

1:16:22

Applied Machine Learning 2019 - Lecture 09 - Gradient boosting; Calibration

1:18:29

Applied Machine Learning 2019 - Lecture 08 - Trees, Forests and Ensembles

1:17:39

Applied Machine Learning 2019 - Lecture 07 - Linear Models for Classifications, SVMs

1:15:59

Applied Machine Learning 2019 - Lecture 06 - Linear Models for Regression

1:17:09

Applied Machine Learning 2019 - Lecture 05 - Preprocessing

1:17:55

Applied Machine Learning 2019 - Lecture 04 - Introduction to supervised learning

1:17:12

Applied Machine Learning 2019 - Lecture 03 - Visualization and Matplotlib

1:14:41

Applied Machine Learning 2019 - Lecture 02 - Version control and Testing

1:23:22

Applied Machine Learning 2019 - Lecture 01 - Introduction to Machine Learning

3:14

A short history of scikit-learn

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