Amazon Makes Internal Machine-Learning Courses Public

Amazon has published videos and supplementary materials from several of its internal Machine Learning University courses. The course lectures cover three machine-learning topics and can be watched on-demand on YouTube, while the slides, notebooks, and datasets can be downloaded from GitHub. A total of twelve courses are planned to be released by the end of the year.

Amazon has published videos and supplementary materials from several of its internal Machine Learning University courses. The course lectures cover three machine-learning topics and can be watched on-demand on YouTube, while the slides, notebooks, and datasets can be downloaded from GitHub. A total of twelve courses are planned to be released by the end of the year.

Amazon announced the release of the courses in a recent blog post. The initial release consists of three "accelerated" courses, which all provide introductions to ML, then progress to the more specialized topics of tabular data, natural language processing (NLP), and computer vision (CV). Each class's video lectures are organized into playlists on YouTube, and supplemental material, including slide decks, datasets, and Jupyter notebooks are available from dedicated GitHub repositories. Nine additional "in-depth" classes are planned by the end of the year. The company initiated its internal Machine Learning University (MLU) as a way to help meet the demand for engineers with ML skills, and according to Amazon Web Services (AWS) research scientist Brent Werness,

By going public with the classes, we are contributing to the scientific community on the topic of machine learning, and making machine learning more democratic.

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