Virtual Practice Labs     Virtual CodeX     CodeX

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Perform architecting tasks such as binning data, imputing values, performing cross validation and evaluating a classification model. Then, test your skills by answering assessment questions after validating a model, tuning parameters, refactoring a machine learning model, and saving and loading models using Python.
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 Engineer track of the Aspire Machine Learning Architect Journey.

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