Calculus

Calculus for AI & ML

This course includes

4 articles

23 mins reading time

11 videos • 5 hr 13 mins

Calculus Fundamentals 8 Topics, Read: 10 mins, 4 Videos: 2 hr 7 mins

Integration

Differentiation

Rules of Differentiation

Limits

Continuity

Differentiability

Maxima & Minima

Saddle Point

Integration for Machine Learning | Simple Explanation with Intuition | Calculus Watch 12 mins

Differentiation | Derivative as Slope & Rate of Change | Derivation of dy/dx formula | Explained Watch 15 mins

Maxima & Minima | Critical Point | Second Order Derivative (Hessian) Test | Explained with Examples Watch 16 mins

Optimization 5 Topics, Read: 8 mins, 5 Videos: 2 hr 6 mins

Loss Function

Convexity

Optimization

Constrained Optimization

Loss Function | Cost Function | Why Squared Error is the preferred Loss Function? | Explained Watch 11 mins

What is Convexity ? | Convex Function Equation | Explained with Example Watch 4 mins

Optimization in Machine Learning | Loss Minimization as Optimization Problem | Explained w\ Examples Watch 8 mins

Constrained Optimization | Lagrangian Method | Lagrange Multiplier | Explained with Example Watch 15 mins

Gradient Descent 4 Topics, Read: 3 mins, 1 Video: 30 mins

Gradient Based Optimization

Batch Gradient Descent (BGD)

Stochastic Gradient Descent (SGD)

Mini Batch Gradient Descent (MBGD)

Gradient Descent | Batch Gradient Descent | Stochastic Gradient Descent |Mini Batch Gradient Descent Watch 30 mins

Newton's Method 3 Topics, Read: 2 mins, 1 Video: 28 mins

Newton's Method

Limitations of Newton's Method

Newton's Method of Optimization | Machine Learning | Explained with Example Watch 28 mins