Theory

Here, you will learn the conceptual and mathematical framework that powers machine learning and artificial intelligence.

Recommended sequence:

1. Intro to Machine Learning
2. Optimization & Gradient Descent
3. Evaluation Basics
4. Feature Engineering Basics
5. Artificial Neural Networks
6. Natural Language Processing
7. Reinforcement Learning

Use the Learning Path for async pacing.

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Table of contents

• 1. Intro to Machine Learning
• 2. Optimization & Gradient Descent
• 3. Artificial Neural Networks
• 4. Natural Language Processing
• 5. Reinforcement Learning
• 6. Evaluation Basics
• 7. Feature Engineering Basics