MXNet R Tutorials
======================
These tutorials for the **mxnet** R package aim to teach both practical usage of neural networks in R as well as the basic internal building blocks of MXNet.
Each tutorial is a self-contained Juypter Notebook which you can run and modify yourself; simply download all the Notebooks into a local folder by clicking `here `_.
.. toctree::
:maxdepth: 1
:titlesonly:
fiveMinutesNeuralNetwork
DigitsClassification
ClassifyImageWithPretrainedModel
charRnn
TimeSeriesLSTM
ndarray
symbol
CallbackFunction
CustomLossFunction
CustomIterator
**Note**: To run the `tutorial Notebooks `_ on your own machine, you must first install the **mxnet** R package plus `Jupyter Notebook with the R kernel `_. Subsequently tell Juypter to use the R kernel after opening each tutorial notebook (after opening the notebook, click on: ``Kernel`` > ``Change Kernel``> ``R``).
More tutorials and examples are available in the `GitHub repository `_.
For more information about MXNet, check out the `main website `_.
The textbook `Dive into Deep Learning `_ is another good resource to learn about the mathematical concepts underlying neural networks and machine learning.