Machine Learning Foundations: Calculus

Learn the basics of calculus concepts and techniques used to design and implement ML algorithms.

Introduction

• Learn calculus foundation for machine learning
• What you should know

1. Introduction to Calculus

• Defining calculus
• Applications of calculus in ML
• Functions
• Limits

2. Derivatives and Differentiation

• Introduction to derivatives
• The derivative of a constant and the power rule
• The constant multiple rule
• The sum rule
• The product rule
• The quotient rule
• The chain rule
• The power rule on a function chain

3. Multivariate Calculus

• Partial derivatives
• Calculating partial derivatives
• Higher-order partial derivatives
• The chain rule for partial derivatives

4. Machine Learning Gradients

• Single-point regression gradient
• The partial derivatives of quadratic cost
• Connecting partial derivatives with backpropagation
• Finding minima and maxima

5. Introduction to Integral Calculus

• Defining integral calculus
• Integration rules
• Indefinite integrals
• Definite integrals

Conclusion

• Next steps