W4995 Applied Machine Learning
This class offers a hands-on approach to machine learning and data science.
machine-learning applied-machine-learning columbia w4995 course tutorial article code video

The class discusses the application of machine learning methods like SVMs, Random Forests, Gradient Boosting and neural networks on real world dataset, including data preparation, model selection and evaluation. This class complements COMS W4721 in that it relies entirely on available open source implementations in scikit-learn and tensor flow for all implementations. Apart from applying models, we will also discuss software development tools and practices relevant to productionizing machine learning models.

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Scikit-learn core-developer, Research Scientist at the Columbia Data Science Institute.
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