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Deep Learning and Machine Learning Guide: Part III

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Deep Learning and Machine Learning Guide: Part III

Step 0 is to learn and use Python. Then, get started with learning about Pytorch. Taking courses, reading books, and trusting machines are key to your success.

· Big Data Zone ·
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Hortonworks Sandbox for HDP and HDF is your chance to get started on learning, developing, testing and trying out new features. Each download comes preconfigured with interactive tutorials, sample data and developments from the Apache community.

Take a Course!

This link is a good start. There's lots of them.

Read a Book!   

I can highly recommend Deep Learning: A Practioner's Approach. From a preview of this, it's extremely well-written and easy to follow — and includes lots of code examples. It is by the brilliant minds of the Deep Learning 4J people.

Trust Machines!  

They wrote that.

The Big Ones: MXNet, TensorFlow, and Keras

Early Preview of PyTorch

Time for me to OSX it!   

pip install https://s3.amazonaws.com/pytorch/whl/torch-0.1.9.post2-cp27-none-macosx_10_7_x86_64.whl 
pip install torchvision 

Every good framework needs examples and tutorials, especially when it is something uber complex like Machine Learning or Deep Learning. Pytorch is new but already has a good introductory set of examples and tutorials to learn from and expand to.

Yet Another Framework and Variation, Chainer v2

Install easily in Python with PIP:

pip install chainerrl

References

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Topics:
deep learning ,machine learning ,big data ,python

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