This repository houses all guided projects I have written during the Machine Learning A-Z course on Udemy.
Course Details
The course aims to fulfill the following learning objectives:
- Master Machine Learning on Python & R
- Have a great intuition of many Machine Learning models
- Make accurate predictions
- Make powerful analysis
- Make robust Machine Learning models
- Create strong added value to your business
- Use Machine Learning for personal purpose
- Handle specific topics like Reinforcement Learning, NLP and Deep Learning
- Handle advanced techniques like Dimensionality Reduction
- Know which Machine Learning model to choose for each type of problem
- Build an army of powerful Machine Learning models and know how to combine them to solve any problem
Jupyter Notebooks and Python files are personally written while .csv data files are provided by the course.
- Part 1 - Data Preprocessing
- Part 2 - Regression
- Part 3 - Classification
- Part 4 - Clustering
- Part 5 - Association Rule Learning
- Part 6 - Reinforcement Learning
- Part 7 - Natural Language Processing
- Part 8 - Deep Learning
- Part 9 - Dimensionality Reduction
- Part 10 - Model Selection & Boosting