Introduction to deep learning with Python
We start with an overview of the basicspandas
and scikit-learn
to pre-process our data and perform simple machine learning tasks. We then dive into Keras
with tensorflow
backend and focus on some of the most common applications of deep learning.
This repository can be accessed via this short link:
- Deep Learning with Python (2nd edition) by François Chollet
- Python Data Science Handbook by Jake VanderPlas
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Some content of a handful of notebooks come from Python Data Science Handbook or A Whirlwind Tour of Python by Jake VanderPlas (under the MIT license. Read more at the Open Source Initiative). Modifications and updates have been made.
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The content of notebook 02-Exploratory-Data-Analysis.ipynb comes primarily from a Kaggle notebook by Aguiar.
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Notebooks on deep learning are corresponding chapters of Deep Learning with Python (2nd edition)