If you feel overwhelmed or have questions, ask on our slack!

• First, Download python. Before doing so, you can check to see if you already have Python installed by opening a Terminal (Mac or Linux) or Command Prompt (Windows) and typing python or python3. If a shell opens, note the version number. For Tensorflow to work effectively, we recommend using at least Python 3.6.7.
• Once you have Python installed, pip should be installed by default. Try the following commands to install OpenAI Gym: pip install gym. If this doesn’t work, try the variants: python -m pip install gym or py -m pip install gym or pip3 install gym. This will be dependent upon what command you type in the shell to make Python run.
• Once you have Gym installed, begin working through the Documentation tutorial. To get the code running, we recommend either using Wing101 Ide, Visual Studio Code, or Sublime Text Editor.
• For two more non-standard IDE’s, consider using Atom, Jupyter Notebook, or Vim. For the latter, type pip install jupyter [see variants above].
• If you want some fun challenging exercises in Python to start playing around, consider
  • GitHub Learning Lab
  • Code Academy
  • Learn Python Tutorials
  • Challenging exercise
• After this, we began working through this series of OpenAI Gym tutorials. We went through the first two steps of making the initial population.
• To apply neural networks, we have to then use Tensorflow. For the basics of Tensorflow:
  • Tutorials Page
  • Adventures in Machine Learning:
    • Tensorflow
    • Neural Networks
    • Deep Q Learning.
  • Keras Activation

• Google Dataset Search
• From hands-on ML by Geron:
  • Open Repos
    • UC Irvine ML Repo
    • Kaggle datasets
    • AWS datasets
  • Meta portals
    • Data Portals
    • OpenDataMonitor
    • Quandl
  • Others
    • Wikipedia
    • Quora
    • Subreddit
• Wikipedia main one