[NeurIPS 2021] Official implementation of the paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"
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Updated
May 18, 2024 - Python
[NeurIPS 2021] Official implementation of the paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"
Observatoire du Plan Vélo
Visualization and Prediction model of Paris traffic ( random Forests ) from data published by the OpenData-Paris project
CLI interface for https://www.paybyphone.fr/
Statistical analysis of incident probability and causes on RATP metro/RER lines
Transilien (parisian public transport) timetables on LCD display.
Our application is a Python-based web scraper that monitors rental listings on real estate agency websites in Paris, France. Users can set their preferred criteria, such as location, price range, number of bedrooms, and other amenities. The scraper runs periodically to check for new listings that match the user's criteria.
This project leverages real-time data from Ile-de-France Mobilités (IDFM) to provide an efficient metro navigation system for Paris and Bordeaux (using a simplified dataset). It utilizes graph algorithms to calculate shortest paths, visualize the minimum spanning tree of the metro network, and check network connectivity.
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