Course Information

An in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects.

• Provider: Massachusetts Institute of Technology (MITx)
• MicroMasters® Program: Statistics and Data Science
• Website: Machine Learning with Python: from Linear Models to Deep Learning (6.86x)
• Start date: Jun 11, 2019
• End date: Sep 4, 2019
• Expected outcomes:
  • Understand principles behind machine learning problems such as classification, regression, clustering, and reinforcement learning
  • Implement and analyze models such as linear models, kernel machines, neural networks, and graphical models
  • Choose suitable models for different applications
  • Implement and organize machine learning projects, from training, validation, parameter tuning, to feature engineering.
• Learning track: audit (non-verified)

Run a Jupyter notebook in Google Colaboratory

The following ways can be used to load a GitHub-hosted notebook into Google Colaboratory.

• Use this GitHub repository's url (subsequent GitHub sign-in is required) to open the notebook directly from GitHub.
• Click on the badge on the top of the GitHub notebook displayed on the website (subsequent GitHub sign-in is required).
• Save the notebook to Google Drive, then open it from Google Drive.
• Download the notebook to your computer/device, then upload it to Google Colab.

To learn more about loading and saving GitHub-hosted notebooks with Google Colab, please visit Using Google Colab with GitHub.