10 Algorithms Every Programmer Should Know – and When to Use Them

@tachyeonz : Programmers love algorithms. What’s an algorithm? Good question! In my academic days, we would have said, “An algorithm is a well-defined, self-contained process or set of rules to be followed in a data processing system.”

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Exploring LSTMs

@tachyeonz : The first time I learned about LSTMs, my eyes glazed over. Not in a good, jelly donut kind of way.

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What my deep model doesn’t know…

@tachyeonz : I come from the Cambridge machine learning group. More than once I heard people referring to us as “the most Bayesian machine learning group in the world”. I mean, we do work with probabilistic models and uncertainty on a daily basis.

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How to use Windows-10 WSL — (Built In Linux) for Machine Learning !

@tachyeonz : A large number of open source libraries\modules in machine learning are first made available for Linux and the windows versions are always released later . Maintaining two separate OS on Dual boot or switching between Virtual machines is not the best way.

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Scaling Airbnb’s Experimentation Platform

@tachyeonz : At Airbnb, we are constantly iterating on the user experience and product features. This can include changes to the look and feel of the website or native apps, optimizations for our smart pricing and search ranking algorithms, or even targeting the right content and timing for our email campaigns.

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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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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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Data scientists compete to create cancer-detection algorithms

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

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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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Try Deep Learning in Python now with a fully pre-configured VM

@tachyeonz : I love to write about face recognition, image recognition and all the other cool things you can build with machine learning. Whenever possible, I try to include code examples or even write libraries/APIs to make it as easy as possible for a developer to play around with these fun technologies.

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