This post is about listing down free online course materials for deep learning (PyTorch) by none other than Yann LeCun. Here are some useful links to the deep learning course:
- Deep Learning course – Homepage
- Deep learning lecture slides
- Github pages having Jupyter notebooks having PyTorch code
Lectures slides, notebooks and related YouTube videos can be found on the deep learning (DL) course home page. It is a 14 week course and covers different topics such as following:
- Introduction to deep learning (What DL can do, what are good features / representations)
- Gradient descent and back propagation algorithm
- Artificial neural networks
- Convolution neural networks (Convnets) and related applications
- Regularization / Optimization techniques and how DL works
- Deep learning architectures
- Energy based models
- Autoencoders
- Generative adversarial networks (GAN)
- Self-supervised learning
- Deep learning for NLP
- Graph convolution networks
Here is the introductory video on Deep Learning by Yann LeCun.
Yann LeCun is currently Silver Professor of Data Science at New York University (NYU). Find some other interesting machine learning projects on this page – Center of Data Science at NYU. You could find everything about Yann LeCun on his page – http://yann.lecun.com/
I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning and BI. I would love to connect with you on Linkedin.
Check out my books titled as Designing Decisions, and First Principles Thinking.
Check out my books titled as Designing Decisions, and First Principles Thinking.
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I found it very helpful. However the differences are not too understandable for me