Introduction to Machine Learning

Duke University
via Coursera
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This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction. In addition, we have designed practice exercises that will give you hands-on experience implementing these data science models on data sets. These practice exercises will teach you how to implement machine learning algorithms with PyTorch, open source libraries used by leading tech companies in the machine learning field (e.g., Google, NVIDIA, CocaCola, eBay, Snapchat, Uber and many more).

Instructor(s)

Lawrence Carin, David Carlson, Timothy Dunn, Kevin Liang
Duke University
via Coursera
Free (audit)
English
Paid Certificate Available
Approx. 26 hours to complete
Self paced
Intermediate Level
Subtitles: Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish