#!/usr/bin/env python
# coding: utf-8

# # Python Notebooks for MXNet
# 
# The outline of python notebooks.
# 
# ## Tutorials
# 
# - [MNIST](./tutorials/mnist.ipynb): Recognize handwritten digits with multilayer perceptrons and convolutional neural networks
# - [Recognize image objects](./tutorials/predict_imagenet.ipynb) with pre-trained model on the full Imagenet dataset that containing more than 10M images and over 10K classes
# - [Char-LSTM](./tutorials/char_lstm.ipynb): Generates Obama's speeches with character-level LSTM.
# - [Matrix Factorization](./tutorials/matrix_factorization.ipynb): Recommend movies to users. 
# 
# ## Basic Concepts
# 
# - [NDArray](./basic/ndarray.ipynb): manipulating multi-dimensional array 
# - [Symbol](./basic/symbol.ipynb): symbolic expression for neural networks
# - [Module](./basic/module.ipynb) : intermediate-level and high-level interface for neural network training and inference. 
# - [Loading data](./basic/data.ipynb) : feeding data into training/inference programs
# - [Mixed programming](./basic/mixed.ipynb): developing training algorithms by using NDArray and Symbol together.
#  
# 
# ## How Tos
# 
# - [Use pretrained models for prediction and feature extraction](./how_to/predict.ipynb) 
# - [Use pretrainde models for fine-tune](./how_to/finetune.ipynb)
# 

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