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Here’s a digest of tutorials, blogs, videos and announcements about Apache
MXNet during July 2018.



94% accuracy on CIFAR-10 in 10 minutes with Amazon SageMaker
<https://medium.com/apache-mxnet/94-accuracy-on-cifar-10-in-10-minutes-with-amazon-sagemaker-754e441d01d7>

Distributed training and the newest algorithmic developments result in
impressive training times for computer vision.



Leveling up on Sagemaker
<https://medium.com/apache-mxnet/leveling-up-on-sagemaker-c7a5a438f0f6>

The Sagemaker series continues with a deep dive on advanced topics related
to MXNet on Sagemaker.



ONNX Model Zoo: Developing a face recognition application with ONNX models
<https://medium.com/apache-mxnet/onnx-model-zoo-developing-a-face-recognition-application-with-onnx-models-64eeeddb9c7a>

A worked example of using a model in the ONNX interchange format from the
Model Zoo to do face recognition.



Scalable multi-node deep learning training using GPUs in the AWS Cloud
<https://aws.amazon.com/blogs/machine-learning/scalable-multi-node-deep-learning-training-using-gpus-in-the-aws-cloud/>

Take AWS infrastructure to the max for distributed training.



GluonNLP — Deep Learning Toolkit for Natural Language Processing
<https://medium.com/apache-mxnet/gluonnlp-deep-learning-toolkit-for-natural-language-processing-98e684131c8a>

A toolkit of word embeddings, state-of-the-art implementations of models
from the latest research papers, and utility functions for the common
datasets.



Logistic regression using Gluon API explained
<https://mxnet.incubator.apache.org/tutorials/gluon/logistic_regression_explained.html>

A step-by-step tutorial on implementing logistic regression using Gluon.



Let Sentiment Classification Model speak for itself using Grad CAM
<https://medium.com/apache-mxnet/let-sentiment-classification-model-speak-for-itself-using-grad-cam-88292b8e4186>

Visualizing the inner workings of a movie review sentiment classification
model.



A Way to Benchmark Your Deep Learning Framework On-premise
<https://medium.com/apache-mxnet/let-sentiment-classification-model-speak-for-itself-using-grad-cam-88292b8e4186>

SK Telecom discusses how they systematically evaluated several deep
learning frameworks, and why they chose MXNet.

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