This repository contains all the code used in the course.

• Module 1: DL Fundamentals: class/Fundamentals
  • NN_Fundamentals: Introduction to TensorFlow, Sequential and Functional API.
  • Prevent_Overfitting: Regularization Techniques.
• Module 2: Convolutional NN: class/CNN
  • Introduction_to_CNN.ipynb: Introduction to CNN & Image Processing.
• Module 3: Recurrent NN: class/RNN
  • Introduction_to_RNN_Time_Series.ipynb: Introduction to Recurrent Neural Networks Applied to Time series.
• Module 4: NLP with Deep Learning: class/NLP
• Module 5: Generative Models: class/generative

You can run the code locally with Jupyter notebook or with Google Colab

To install TensorFlow and TensorFlow-hub, run:

pip install tensorflow
pip install --upgrade tensorflow-hub

For more details see TensorFlow installation instructions

To install all the dependencies, run:

pip install -r requirements.txt

You can upload the notebook directly in Google Colab or you can click in the Colab icon at the beginning of each notebook:

Run in Google Colab

View Source on GitHub