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Megazord (Backend) is the backend of an industrial pieces image recognition app using deep learning.

License: MIT License

Python 100.00%
computer-vision convolutional-neural-networks deep-learning

megazord-backend's Introduction

Lucas Saban

Quant Researcher @QRT

Previously Double Degree Master student at Ensae Paris and MVA (ENS Paris-Saclay). Interested in Machine Learning, Deep Learning, Swarm intelligence.

I open source some of my projects here.

Currently working on :

  • Quantools : [Financial Engineering | Visualization | High Performance Python] A tool-box for quants (ML-oriented)
  • DDQL : [RL | Optimal Execution | Trading] Implementation of a paper.

Contact : lucas[dot]saban[at]ensae[dot]fr

Awards and Competitions

Some projects

Academy

  • Leveraging latent representations for efficient textual OOD detection. Paper, Repo (Not published)

  • Large scale joint Hyperparameters and feature selection using Multi-objective heuristic optimization Report, Presentation and Repo

  • Implementation of Fast Shapelet discoveries for time series classification Orignal Paper, Report and Repo

  • Implementation of Double Deep Q-Learning for Optimal Trading Execution Orignal Paper, Report and Repo

Industry

  • Spatio-temporel spectral clustering algorithm based on HDBSCAN for dynamic event recognition. Source is private but happy to talk about it.

  • A full-stack Image Classification project using Tensorflow, Transfer-learning and CNN's. An iOS app, that I coded in swift, is the front-end part of the project. It was realized with Augustin Cramer

Demo

  • A scikit-learn plugin for binary Classification tasks, delivered as a pypi package. The source is available here.

TAM_logo

Demo

The ants adapt to the change in their environnement. They quickly find a new path following the pheromones tracks.

gRavlaw

megazord-backend's People

Contributors

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Stargazers

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Watchers

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Forkers

augustin-cramer

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