Virtual Practice Labs     Virtual CodeX     CodeX

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Perform DL programming tasks with Python, such as performing series expansion and calculus, and work with Tensorflow and scikit-image. Then, test your skills by answering assessment questions after loading a data set for hierarchical clustering and k-means clustering, and train a model using random forests and gradient boosting.
This lab provides access to several tools commonly used in machine learning, including:
Microsoft Excel 2016
Visual Studio Code
Anaconda
Jupyter Notebook + JupyterHub
Pandas, NumPy, SiPy
Seaborn Library
Spyder IDE
This lab is part of the DL Programmer track of the Aspire Machine Learning Architect Journey.

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