Top 15 Python Libraries for Data Science in 2017

@tachyeonz : As Python has gained a lot of traction in the recent years in Data Science industry, we wanted to outline some of its most useful libraries for data scientists and engineers, based on our experience.

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Build a super fast deep learning machine for under $1,000

@tachyeonz : Register for the O’Reilly Artificial Intelligence Conference, June 26-29 in New York City. Yes, you can run TensorFlow on a $39 Raspberry Pi, and yes, you can run TensorFlow on a GPU powered EC2 node for about $1 per hour.

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Nasa runs competition to help make old Fortran code faster

@tachyeonz : Nasa is seeking help from coders to speed up the software it uses to design experimental aircraft. It is running a competition that will share $55,000 (£42,000) between the top two people who can make its FUN3D software run up to 10,000 times faster.

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donnemartin/system-design-primer

@tachyeonz : Learn how to design large-scale systems. Prep for the system design interview.

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Rohan & Lenny #3: Recurrent Neural Networks & LSTMs

@tachyeonz : It seems like most of our posts on this blog start with “We’re back!”, so… you know the drill. It’s been a while since our last post — just over 5 months — but it certainly doesn’t feel that way.

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Dive into Deep Learning with 12 free online courses

@tachyeonz : Every day brings new headlines for how deep learning is changing the world around us. A few examples:

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How to get started with machine learning in manufacturing

@tachyeonz : Smart machines are changing the way we manufacture. Machine learning, a type of artificial intelligence that gives machines the ability to learn without human help, creates new connections between manufacturing design and technologies like augmented reality.

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The Cost of Doing Data Science on Laptops

@tachyeonz : At the heart of the data science process are the resource intensive tasks of modeling and validation. During these tasks, data scientists will try and discard thousands of temporary models to find the optimal configuration. Even for small data sets, this could take hours to process.

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Variational Autoencoder: Intuition and Implementation

@tachyeonz : There are two generative models facing neck to neck in the data generation business right now: Generative Adversarial Nets (GAN) and Variational Autoencoder (VAE). These two models have different take on how the models are trained.

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Data scientists compete to create cancer-detection algorithms

@tachyeonz : Data scientists are using machine learning to tackle lung cancer detection.

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Building GCC 7 on Windows Subsystem for Linux

@tachyeonz : In this article, I will show you how to compile from sources GCC 7.1 on WSL, Windows Subsystem for Linux. The default version of GCC, at the time of this writing, is 5.4 which is pretty old. GCC 7.1 has complete support for C++11, C++14 and experimental support for the current C++17 draft. GCC 7.

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Make your data science projects reproducible and shareable.

@tachyeonz : DVC derives the DAG (dependency graph) transparently to the user.

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