Course
In this course, you’ll learn the fundamental mathematical concepts behind some of the most important machine learning algorithms: calculus. As a data scientist, you’ll need to understand the fundamentals of calculus for algorithms like the gradient descent algorithm and backpropagation to train deep learning neural networks.
Part of the Data Scientist, and Machine Learning Introduction with Python paths.
4.8 (359 reviews)
8,771 learners enrolled in this course.
- Intermediate friendly
- 2 hours
- Self paced
- 3 lessons
“Dataquest teaches you how you do data analysis in the real world. Dataquest is well-suited for folks with busier schedules. The lessons are broken into smaller chunks, so it’s really conducive to that. You only have an hour, okay, well, just do one or two lessons and that’s fine.”
Ashray Adappa
Data Analyst Consultant @Fractal
Calculus For Machine Learning
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
- Decompose a linear equation into slope and y-intercept
- Define slope
Understanding Limits 1h
- Represent slope using limits
- Define defined and undefined limits
- Compute limits using SymPy
Finding Extreme Points 1h
- Identify extreme points in a nonlinear function
- Compute the derivative of a nonlinear function
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