example/sparse/README.md

<!--- Licensed to the Apache Software Foundation (ASF) under one -->
<!--- or more contributor license agreements.  See the NOTICE file -->
<!--- distributed with this work for additional information -->
<!--- regarding copyright ownership.  The ASF licenses this file -->
<!--- to you under the Apache License, Version 2.0 (the -->
<!--- "License"); you may not use this file except in compliance -->
<!--- with the License.  You may obtain a copy of the License at -->

<!---   http://www.apache.org/licenses/LICENSE-2.0 -->

<!--- Unless required by applicable law or agreed to in writing, -->
<!--- software distributed under the License is distributed on an -->
<!--- "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY -->
<!--- KIND, either express or implied.  See the License for the -->
<!--- specific language governing permissions and limitations -->
<!--- under the License. -->

# Examples using Sparse Symbol API
This folder contains examples that demonstrate the usage of [Sparse Symbol API](https://mxnet.incubator.apache.org/api/python/symbol/sparse.html)
- [Factorization Machine](https://github.com/apache/incubator-mxnet/tree/master/example/sparse/factorization_machine) uses sparse weights
- [Linear Classification Using Sparse Matrix Multiplication](https://github.com/apache/incubator-mxnet/tree/master/example/sparse/linear_classification) shows how to use a sparse data loader, sparse dot operator and sparse gradient updaters
- [Matrix Factorization w/ Sparse Embedding](https://github.com/apache/incubator-mxnet/tree/master/example/sparse/matrix_factorization) uses sparse weights
- [Wide and Deep Learning](https://github.com/apache/incubator-mxnet/tree/master/example/sparse/wide_deep) shows how to run sparse wide and deep classification