This repository contains Jupyter notebooks implementing the code samples found in the book Deep Learning with Python (Manning Pubblications) by François Chollet, gathered by chapter.
The author already published notebooks with the exercises in his Github account. Those you can find in this repository are made by myself for my own learning, with no intention so steal any intellectual property.
- Create a virtual environment with
conda
orvirtualenv
. Recommendedconda
with Python 3.6.
conda create --name <your_project> python=3.6
- Install dependencies:
pip install -r requirements.txt
The exercises in the book are written for tensorflow 1.*
and Keras 2.0.8
. All the code in this repo have been rewritten to work with tensorflow 2.1.*
and the corresponding Keras version 2.2.4-tf
.
No relevant exercises
- 01: a first look at a neural network - notebook
- 01: binary classification - notebook
- 02: multiclass classification - notebook
- 03: logistic regression - notebook
- 01: binary classification: mitigate overfitting and underfitting - notebook
- 01: introduction to CNN - notebook
- 02: using CNNs with small datasets - notebook
- 03: using a pretrained CNN - notebook
- 04: visualizing what a CNN learn - notebook
- 01: one-hot encoding of words or characters - notebook