Tuatini's blog

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GODARD Tuatini

  1. [Part 2] From deep learning papers implementation to shipping models into production

    While developing a product from scratch based on deep learning you always end up asking you this question: "How will I ship and maintain my deep learning models in production?". Given you are a data scientist or a deep learning researcher, maintaining deployed products is by far the…

  2. [Part 1] From deep learning papers implementation to shipping models into production

    If you are a data scientist or a deep learning researcher, maintaining deployed products is by far the less exciting part of the process. In this guide, I'll show you how I managed to ship my image super-resolution project with minimal devops and maintenance.…

  3. SuperDatascience podcast

    Here is my in interview with Kirill Eremenko from SuperDatacience where we discuss various things around Data science/AI.…

  4. Practical image segmentation with Unet

    Introduction In this post we will learn how Unet works, what it is used for and how to implement it. To do so we will use the original Unet paper, Pytorch and a Kaggle competition where Unet was massively used. If you don't know anything about Pytorch, you are afraid…

  5. Building TensorFlow 1.3.0 as a standalone project (Raspberry pi 3 included)

    Here you'll learn how to build Tensorflow either for your x86_64 machine or for the raspberry pi 3 as a standalone shared library which can be interfaced from the C++ API. (This tutorial couldn't be possible without the help of the people from the References section) Watch out for…

  6. [Part 2] How to setup your own environment for deep learning - For remote access

    Introduction and goal In part 1 we learned how to setup your computer locally for deep learning. Now imagine you're like me and you usually work on your laptop but you still want to use your computer with a powerful GPU whenever you want from anywhere in the world, in…