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
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.
Note: The entire tutorial is π interactive, β auto-graded and with πΉ video tutorials.
These exercises were built in collaboration; we need you! If you find any bugs or misspellings, please contribute and report them.
Thanks to these wonderful people (emoji key):
Alejandro Sanchez (alesanchezr), contribution: (coder) π», (idea) π€, (build-tests) β οΈ, (pull-request-review) π, (build-tutorial) β , (documentation) π
Paolo (plucodev), contribution: (bug reports) π, (coder) π», (translation) π
Ricardo Rodriguez (RickRodriguez8080) contribution: (build-tutorial) β , (documentation) π
This project follows the all-contributors specifications.
Contributions of any kind are welcome!
Difficulty
intermediate
Average duration
10 hrs
Difficulty
intermediate
Average duration
10 hrs