Prerequisites: Familiarity with Python programming and basic algebra.

Level: Intermediate

What You'll Learn

• Differential Calculus Fundamentals

  Understand limits, derivatives, and differentiation rules for single-variable functions.

• Calculus in Optimization

  Apply derivatives to find function minima/maxima, forming the basis for model optimization.

• Multivariable Calculus Concepts

  Grasp partial derivatives, gradients, and the Hessian matrix for functions with multiple inputs.

• Gradient-Based Optimization

  Understand the mechanics of gradient descent and its variants used in training machine learning models.

• Calculus in Neural Networks

  Recognize the role of the chain rule in the backpropagation algorithm for training deep learning models.

• Practical Application

  Implement calculus concepts using Python libraries like NumPy for ML-related tasks.