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Introduction


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Introduction

The problem with Dropout on images


Photo by Eric TERRADE on Unsplash. The most famous face in the world!

A deep learning approach

  • a find faces algorithm
  • a way to embed the faces in vector space
  • a function to compare the encoded faces

Find Faces


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torchserve to the rescue!

  1. Installation with Docker
  2. Export your model
  3. Define a handler
  4. Serve our model

Installation with Docker

docker pull pytorch/torchserve:latest


A semantic browser using deep learning and elastic search to search COVID papers


A clean and simple template to kick start your next dl project 🚀🚀

  • modularity: we split each logic piece into a different python submodule
  • data-augmentation: we included imgaug
  • ready to go: by using poutyne a Keras-like framework you don’t have to write any train loop.
  • torchsummary to show a summary of your models
  • reduce the learning rate on a plateau
  • auto-saving the best model
  • experiment tracking with comet

Motivation


Introduction


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Module: the main building block

Francesco Zuppichini

“quam minimum credula postero” https://francescozuppichini.carrd.co/

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