In our increasingly tech-driven world, Machine Learning is literally driving the future. In this learning path, you’ll complete workshops on Machine Learning, Supervised Learning, Unsupervised Learning, and Applied AI and Natural Language Processing (NLP).
Once you complete these workshops you’ll be adept at understanding how modern machines learn and how to build optimized systems.
Jump in with Scikit-Learn
INTRODUCTION TO SCIKIT-LEARN
This course covers scikit-learn’s syntax to solve simple data problem, which will be the starting point to develop machine learning solutions.
The Machine Learning Workshop
The Supervised Learning Workshop
The Unsupervised Learning Workshop
The Reinforcement Learning Workshop
- Introduction to Reinforcement Learning
- Introduction to The Markov Decision Process and Dynamic Programming
- Practice Deep Learning with TF2
- Getting Started with OpenAI and TensorFlow for RL
- Introduction to Dynamic Programming
- Introduction to Monte Carlo Methods
- Introduction to Temporal-Difference Learning
- Solving the Multi Armed Bandit Problem
- Introduction to Deep Q Learning
- Playing an Atari Game with a Deep Recurrent Q Network
- Introduction to Policy Based Methods for Reinforcement Learning
- Discussing Evolutionary Strategies for Reinforcement Learning
- Discussing Advancements for Reinforcement Learning