Optimization Techniques for Machine Learning

This course bridges the gap between pure mathematical optimization and continuous real-world applications in Machine Learning. It is delivered for working professionals through BITS Pilani Work Integrated Learning Programmes.

Click the links below to view or download the presentation slides (PDF formats).

• Lecture 1: Analytic Geometry

• Lecture 2: Spectral Theorem

• Lecture 3: Linear Optimization I

• Lecture 4: Linear Optimization II

• Lecture 5: Vector Calculus I

• Lecture 6: Vector Calculus II

• Lecture 7: Continuous Optimization I

• Lecture 8: Continuous Optimization II

• Lecture 9: Duality I

• Lecture 10: Duality II

• Lecture 11: PCA I

• Lecture 12: PCA II

• Lecture 13: Machine Learning I

• Lecture 14: Machine Learning II

• Lecture 15: Time Series Forecasting

• Lecture 16: Recap