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Numpy Tutorial Exercises

This interactive tutorial will help you become familiar on it, master the most used functionalities and help you clean up your first datasets

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Difficulty

  • intermediate

Average duration

10 hrs

Difficulty

  • intermediate

Average duration

10 hrs

Sign up and get access to interactive tutorial

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Difficulty

  • intermediate

Average duration

10 hrs

Difficulty

  • intermediate

Average duration

10 hrs

Difficulty

  • intermediate

Average duration

10 hrs

Difficulty

  • intermediate

Average duration

10 hrs

NumPy (and Pandas) are the #1 libraries for Machine Learning, there is no way you can do anything without them.

This interactive tutorial will help you become familiar with it, master the most used functionalities, and help you clean up your first datasets.

  • NumPy documentation.
  • Vectors.
  • Matrixes.
  • Random, Mean Values.

Note: The entire tutorial is πŸ‘† interactive, βœ… auto-graded and with πŸ“Ή video tutorials.

These exercises were built in collaboration; we need you! If you find any bugs or misspellings, please contribute and report them.

Contributors

Thanks to these wonderful people (emoji key):

  1. Alejandro Sanchez (alesanchezr), contribution: (coder) πŸ’», (idea) πŸ€”, (build-tests) ⚠️, (pull-request-review) πŸ‘€, (build-tutorial) βœ…, (documentation) πŸ“–

  2. Paolo (plucodev), contribution: (bug reports) πŸ›, (coder) πŸ’», (translation) 🌎

  3. Ricardo Rodriguez (RickRodriguez8080) contribution: (build-tutorial) βœ…, (documentation) πŸ“–

This project follows the all-contributors specifications.

Contributions of any kind are welcome!

Sign up and get access to interactive tutorial

We will use it to give you access to your account.
Already have an account? Login here.

By signing up, you agree to the Terms and conditions and Privacy policy.

Difficulty

  • intermediate

Average duration

10 hrs

Difficulty

  • intermediate

Average duration

10 hrs