Pinned Repositories
DisasterMessagesClassifier
The Disaster Response web app enables an emergency worker to classify text messages into 36 non exclusive categories. The web app depicts the contents of the training dataset - i.e.: real messages that were sent during disaster events - trough three visualizations.
ereynrs
ereynrs.github.io
At the Confluence
SciArticlesRecommender
Data is processed, transformed, and loaded into the Neo4j graph database. Using the cleaned and modelled data, authors are disambiguated, recommendations in terms of what authors could review the incoming publications are made, and the most influential authors are identified.
SentimentAnalysisWebapp
Sentiment Analysis Web App deployed in AWS Sagemaker
StarbucksRewardsOptimizer
Data Scientist Nanodegree Program - Starbucks Capstone Project
WatsonStudioArticlesRecommender
recommendation_engines
the-fair-cookbook
The FAIR cookbook, containing recipes to make your data more FAIR. Find the rendered version on:
ereynrs's Repositories
ereynrs/DisasterMessagesClassifier
The Disaster Response web app enables an emergency worker to classify text messages into 36 non exclusive categories. The web app depicts the contents of the training dataset - i.e.: real messages that were sent during disaster events - trough three visualizations.
ereynrs/ereynrs
ereynrs/ereynrs.github.io
At the Confluence
ereynrs/SciArticlesRecommender
Data is processed, transformed, and loaded into the Neo4j graph database. Using the cleaned and modelled data, authors are disambiguated, recommendations in terms of what authors could review the incoming publications are made, and the most influential authors are identified.
ereynrs/SentimentAnalysisWebapp
Sentiment Analysis Web App deployed in AWS Sagemaker
ereynrs/StarbucksRewardsOptimizer
Data Scientist Nanodegree Program - Starbucks Capstone Project
ereynrs/WatsonStudioArticlesRecommender
recommendation_engines