Learn foundational machine learning skills in the Intro to Machine Learning Nanodegree program and learn how to apply these skills to a variety of tasks. In the Machine Learning Engineer Nanodegree program, learn how to create a machine learning product and deploy machine learning models to a production environment, such as a web application.
Build a solid foundation in Supervised, Unsupervised, and Deep Learning. Then, use these skills to test and deploy machine learning models in a production environment.
To optimize your chances of success in this program, we recommend intermediate Python programming knowledge and basic knowledge of probability and statistics.See detailed requirements.
In this lesson, you will learn about supervised learning, a common class of methods for model construction.
Find Donors for CharityML
In this lesson, you’ll learn the foundations of neural network design and training in PyTorch.
Build an Image Classifier
In this lesson, you will learn to implement unsupervised learning methods for different kinds of problem domains.
Create Customer Segments
Cezanne Camacho, Mat Leonard, Luis Serrano, Dan Romuald Mbanga, Jennifer Staab, Sean Carrell, Josh Bernhard , Jay Alammar and Andrew Paster
Start your review of Intro to Machine Learning with PyTorch
"This program so far has exceeded my expectations. First, access to mentors that readily answers questions is so valuable. When learning a new topic it is so easy to get stuck and frustrated, but when you can reach out to someone that can answer your...
"This program so far has exceeded my expectations. First, access to mentors that readily answers questions is so valuable. When learning a new topic it is so easy to get stuck and frustrated, but when you can reach out to someone that can answer your question is really valuable. I have taken other online courses and this is by far the greatest advantage of the course. Second, the concepts are taught in a very intuitive and graphic way. I was shocked at how good concepts were explained. It doesn't delve too deep into the mathematics but does give the student enough to on his own and read more advanced books and progress. The project was just difficult enough that it pushes you, but it is just the right amount that doesn't leave you frustrated, stuck, or confused. I can see that great effort was put into developing this material.
Anonymous is taking this course right now.
very poor content don't worth the money and the time
it even redirect you to Khan Academy Videos and YouTube videos to cover the important parts
It is exceeding my expectations so far. My projects have been promptly reviewed and the feedbacks are extremely thorough and constructive.