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Grokking Deep Learning with Julia

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Grokking Deep Learning with Julia

Grokking Deep Learning with Julia

Grokking Deep Learning with Julia

Date Published

Jul 29, 2020

Jul 29, 2020

Contributors

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Date Published

Jul 29, 2020

Contributors

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Andrew Trask's book Grokking Deep Learning is the perfect place to begin your deep learning journey. It teaches you to build deep learning from scratch rather than just learn the “black box” API of some library or framework. In this book you’ll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare!

The book uses Python and its math-supporting library NumPy to implement convolutional neural networks, RNN, and LSTM. This post is to announce the Julia companion to the book. Julia is a new and promising language that offers the dynamic nature of Python as well as the performance of C/C++.

You can find the Julia notebooks here. Please try them out and file issues if you find any.

Authors

JuliaHub, formerly Julia Computing, was founded in 2015 by the four co-creators of Julia (Dr. Viral Shah, Prof. Alan Edelman, Dr. Jeff Bezanson and Stefan Karpinski) together with Deepak Vinchhi and Keno Fischer. Julia is the fastest and easiest high productivity language for scientific computing. Julia is used by over 10,000 companies and over 1,500 universities. Julia’s creators won the prestigious James H. Wilkinson Prize for Numerical Software and the Sidney Fernbach Award.

Authors

JuliaHub, formerly Julia Computing, was founded in 2015 by the four co-creators of Julia (Dr. Viral Shah, Prof. Alan Edelman, Dr. Jeff Bezanson and Stefan Karpinski) together with Deepak Vinchhi and Keno Fischer. Julia is the fastest and easiest high productivity language for scientific computing. Julia is used by over 10,000 companies and over 1,500 universities. Julia’s creators won the prestigious James H. Wilkinson Prize for Numerical Software and the Sidney Fernbach Award.

Authors

JuliaHub, formerly Julia Computing, was founded in 2015 by the four co-creators of Julia (Dr. Viral Shah, Prof. Alan Edelman, Dr. Jeff Bezanson and Stefan Karpinski) together with Deepak Vinchhi and Keno Fischer. Julia is the fastest and easiest high productivity language for scientific computing. Julia is used by over 10,000 companies and over 1,500 universities. Julia’s creators won the prestigious James H. Wilkinson Prize for Numerical Software and the Sidney Fernbach Award.

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Read the Dyad Documentation – Dive into the language, tools, and workflow.

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