This course introduces you to the core principles of deep learning through hands-on coding in PyTorch. You’ll start by learning how PyTorch represents data with tensors and how datasets and data loaders fit into the training process. Step by step, you’ll build and train neural networks, experiment with different architectures, and explore how models learn from examples. You’ll also learn how to monitor training progress, interpret results, and evaluate performance. By the end of the course, you’ll understand PyTorch’s workflow and be ready to design, train, and test your own neural networks with confidence.
Used the course as a refresher. Nicely paced, along with good intuitive explanations of various tricks (batch norm, maxpooling, etc).
Cover the fundamental in intuitive way, and reinforced it through jupyter notebook.
Provides context knowledge, great course design and good lecture delivery
Very well explained fundamentals on PyTorch and Machine Learning. Much better than any other course I've done on the same subjects.
Really well explained, and clear. Good labs and assignments.
Well structured and packed with awesome resources like fun quizzes, guided labs, and exciting programming assignments!
Very well structured course! I was not lost at any time, thank you!
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Very well explained fundamentals on PyTorch and Machine Learning. Much better than any other course I've done on the same subjects.
It is an interesting course although not that engaging since most of the assignments are to straightforward and making it very easy to pass.
bad
I really enjoyed this course. It is comprehensive, well-structured, and very clear, making the content easy to follow. It goes beyond theory by teaching practical know-how. I especially appreciated how it highlights common mistakes beginners make when using PyTorch, along with best practices to avoid them and clear guidance on how to debug effectively. It also provides a lot of resources to dive deeper. Highly recommended!
This course is a practical hands-on introduction to Pytorch with some knowlegde of python and deep learning is assumed. The lab and programming assignments are very extensive and contains good amount of written explanation to guide through the implementation. Overall a well developed course and I had a great experience learning it.
Laurence Moroney taught this course in an exceptionally professional and engaging manner. I’ve taken several PyTorch courses, and this is easily one of the best - clear, well-structured, and highly practical.
Overall it was very good, I liked it. The only thing that bothered me was watching it with subtitles, but even that wasn't very in-depth, which was my problem.
Used the course as a refresher. Nicely paced, along with good intuitive explanations of various tricks (batch norm, maxpooling, etc).
Well structured and packed with awesome resources like fun quizzes, guided labs, and exciting programming assignments!
Cover the fundamental in intuitive way, and reinforced it through jupyter notebook.
Great course to learn PyTorch! I strongly recommend it for beginners as me
Provides context knowledge, great course design and good lecture delivery
Very well structured course! I was not lost at any time, thank you!
The best PyTorch and might I say deep learning course out there!
Really well explained, and clear. Good labs and assignments.
For the hand on experience this course is awesome
Fantastic intro to Machine Learning. I loved it.
Its Literally Goated Course , Love it ❤️❤️
挺好的，从最基础的张量开始，一点点深入，有可以练手的Lab，为后续课程打下基础
Loved it