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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.

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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


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deep learning ,machine learning ,big data ,python

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