Charles Malafosse

sports-betting-customloss. We present a way to incorporate bets' potential profit into a neural network classifier model using a custom loss function. We believe this to be extremely useful for anyone looking to use machine learning to create a betting system. It is what we do at BetSentiment.com.

open-dataset-for-sentiment-analysis. open datasets for sentiment analysis based on tweets in English/Spanish/French/German/Italian

FastText-sentiment-analysis-for-tweets. Essential about fastText architecture, cleaning, upsampling and sentiments for tweets.

custom-factor-model. Data and R code related to my medium article "Custom Factor Models - Build your own in R with a few lines of codes"

aws-elasticbeanstalk-ml-server. Hands-on meetup - How to Serve machine learning models with AWS ElasticBeanstalk

factor-investing-with-aws-lambda-iex-cloud. Python