R Tutorials¶
These tutorials introduce a few fundamental concepts in deep learning and how to implement them in R using MXNet.
- Callback Function
- Custom Iterator Tutorial
- Customized loss function
- LSTM time series example
- Character-level Language Model using RNN
- Classify Images with a PreTrained Model
- Develop a Neural Network with MXNet in Five Minutes
- Handwritten Digits Classification Competition
- NDArray: Vectorized Tensor Computations on CPUs and GPUs
- Symbol and Automatic Differentiation
More tutorials and examples are available in the GitHub repository.
