Chip Huyen's CS20SI at Stanford: Tensorflow for Deep Learning Research
TensorFlow is open source tools developed by a group of Google Brain researchers and engineers. It is a deep neural networks framework, mainly to build up data flow graphs to deal with numerical operation.
Tensorflow for Deep Learning Research is covering complicated RNN, LSTM in natural language processing, CNN in computer vision applications as well as a small part of Reinforcement Learning.
This class also invited other speakers to explain Convolutional Neural Network, such as Justin Johnson (Stanford Vision Lab) and Lukasz Kaiser (Google Brain)
This course begins with TensorFlow's foundation for deep learning, with the goal of getting students to understand the concept of the computational graph behind Tensorflow and the architecture.
Unfortunately, youtube video is not complete, but all the notes and Slides can be downloaded. Github also have a lot of example implementation in Chatbot and Style Transfer. If you want to learn TensorFlow, Here is the path.
Syllabus : http://web.stanford.edu/class/cs20si/syllabus.html
Github : https://github.com/chiphuyen/tf-stanford-tutorials
Youtube lecture video : https://www.youtube.com/playlist?list=PLIDllPt3EQZoS8gCP3cw273Cq9puuPLTg
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