Pinned Repositories
relax
RelaX - a relational algebra calculator
DeepLearning2
graph-forecast-national-elections
Applied-deep-learning-with-python-project---Sentiment-Analysis
2021-assignment-numpy
Assignment 1 for the DataCamp course X-DataScience Master
2021-assignment-pandas
Assignment 2 for the DataCamp course X-DataScience Master - pandas
2021-assignment-sklearn
Assignment 3 for the DataCamp course X-DataScience Master - scikit-learn API
RaphaelGervillie-graph-forecast-national-elections
2017 French Presidential Elections Forecast : France, like many countries, operates by the system of universal suffrage. During each vote, the results are final when all the votes have finished being counted. But some estimation can be made on the final results during the day. This challenge proposes to explore models allowing to predict the results using only half of the votes. This type of challenge is part of all the economic issues that are seeing a revival with the arrival of machine learning methods. With the increase of available data in open access, it is possible to better model complex economic problems. This challenge therefore aims on the one hand to improve the estimate of the election results and on the other hand to propose an original model allowing to capture the multiple dimensions of this problem.
Superpixel
Superpixel segmentation using SLIC and Felzenszwalb.
RaphaelGervillie's Repositories
RaphaelGervillie/Superpixel
Superpixel segmentation using SLIC and Felzenszwalb.
RaphaelGervillie/2021-assignment-numpy
Assignment 1 for the DataCamp course X-DataScience Master
RaphaelGervillie/2021-assignment-pandas
Assignment 2 for the DataCamp course X-DataScience Master - pandas
RaphaelGervillie/2021-assignment-sklearn
Assignment 3 for the DataCamp course X-DataScience Master - scikit-learn API
RaphaelGervillie/RaphaelGervillie-graph-forecast-national-elections
2017 French Presidential Elections Forecast : France, like many countries, operates by the system of universal suffrage. During each vote, the results are final when all the votes have finished being counted. But some estimation can be made on the final results during the day. This challenge proposes to explore models allowing to predict the results using only half of the votes. This type of challenge is part of all the economic issues that are seeing a revival with the arrival of machine learning methods. With the increase of available data in open access, it is possible to better model complex economic problems. This challenge therefore aims on the one hand to improve the estimate of the election results and on the other hand to propose an original model allowing to capture the multiple dimensions of this problem.