Tutorials & Books
- TensorFlow, Keras and deep learning, without a PhD: A very interesting tutorial for beginners.
- Dive into Deep Learning and its Chinese version. The PyTorch implementation is also available.
- DEEP LEARNING: A new open course from NYU CENTER FOR DATA SCIENCE
- Calculus on Computational Graphs: Backpropagation: A good mathematical background for backpropagation.
- Optimization for Deep Learning Highlights in 2017: A good note for the optimization on deep learning.
- ML Visuals: A new collaborative effort to help the machine learning community in improving science communication by providing free professional, compelling and adequate visuals and figures.
For understanding RNN and LSTM
- The Unreasonable Effectiveness of Recurrent Neural Networks: A good tutorial together with codes.
- Understanding LSTM Networks : From RNN to LSTM, we can get the basic idea of LSTM network.
- Understanding LSTM and its diagrams : A good diagram can describe everything!
- Long Short-Term Memory: From Zero to Hero with PyTorch: A basic description and its code implementation.