This course provides the essential calculus knowledge needed to understand core machine learning concepts. Learn about derivatives, gradients, and optimization principles through clear explanations and practical examples. Build the mathematical foundation required for building and tuning AI models.
Prerequisites Basic algebra concepts
Level:
Function Fundamentals
Understand functions, their representations, and the concept of limits as a basis for calculus.
Derivatives
Calculate derivatives of simple functions and understand their meaning as rates of change.
Optimization Basics
Grasp how derivatives are used to find function minima or maxima, the core idea behind model optimization.
Gradient Descent Intuition
Understand the concept of gradient descent and its role in training machine learning models.
Partial Derivatives
Learn how to calculate partial derivatives for functions with multiple inputs and understand the gradient vector.
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