## Course overview

Calculus is one of the core mathematical concepts behind machine learning, and enables us to understand the inner workings of different machine learning algorithms. It plays an important role in the building, training, and optimizing machine learning algorithms.

In this course, you’ll learn to work with linear and nonlinear functions, including decomposing a linear equation into slope and y-intercept or defining slope. You’ll also learn to use limits, including representing slope using limits, defining defined and undefined limits, and computing limits using SymPy. Finally, you’ll identify extreme points in a nonlinear function and compute the derivative of a nonlinear function.

Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser.

## Key skills

- Defining mathematical functions using calculus
- Employing intermediate machine learning techniques

## Course outline

### Calculus For Machine Learning [3 lessons]

### Understanding Linear and Nonlinear Functions 1h

Lesson Objectives- Decompose a linear equation into slope and y-intercept
- Define slope

### Understanding Limits 1h

Lesson Objectives- Represent slope using limits
- Define defined and undefined limits
- Compute limits using SymPy

### Finding Extreme Points 1h

Lesson Objectives- Identify extreme points in a nonlinear function
- Compute the derivative of a nonlinear function

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