This repository houses all guided projects I have written during the Deep Learning A-Z course on Udemy.
Course Details
The course aims to fulfill the following learning objectives:
Understand the intuition behind and apply the following in practice:
- Artificial Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Self-Organizing Maps
- Boltzmann Machines
- AutoEncoders
Jupyter Notebooks and Python files are personally written while .csv data files are provided by the course.
Note: ANN and CNN projects are the same as in Part 8 of the Machine Learning A-Z course.
- Part 0 - Data Preprocessing
- Part 1 - Artificial Neural Networks: Bank Customer Churn Analysis
- Part 2 - Convolutional Neural Networks: Dog/Cat Classifier
- Part 3 - Recurrent Neural Networks: Google Stock Price Prediction
- Part 4 - Self-Organizing Maps
- Part 5 - Boltzmann Machines
- Part 6 - AutoEncoders