Wine has recently generated a lot of interest among private investors. The wine market, like the wine itself, is maturing with age. More experienced players, investable wines, and an increasing desire from individuals all around the world! …

A concise explanation on why increasing the memory amount of a AWS Lambda function might actually save you money Are you building a web app or API? Or do you need to run serverless code? AWS Lambda is a great option. You only pay for what you use and you…

When risk managers or quant professionals need to compare different metric types or normalize data, z-scores are their go-to measure. In theory, Z-scores are powerful and easy to understand. In practical use, however, they have two strong limitations that can affect their interpretation: A high sensitivity to the distribution of…

A step-by-step guide to build your own fundamental factor model using R and cross-sectional regressions — Multi-factor models are a must-have for investors looking to understand their portfolio’s performance drivers. It helps explain the actual return of factors such as countries, sectors, and styles, independent of other factors’ effects. In this article, we will focus on the mechanics of such models, and how to code them…

A short guide to fast track your journey on AWS Lambda and save money and time — AWS Lambda is quite simple to use but as the same time it can be tricky to implement and optimize. In this post I summarized 3 years of experience working with this service. The result is a list of 7 things I wish I already knew when I started, from…

A complete guide to serve a sentiment analysis model using AWS Elastic Beanstalk — We present a comprehensive procedure to serve a FastText sentiment analysis model using AWS Elastic Beanstalk. We provide all you need to get your own on-demand sentiment analysis service in 5 languages. A lot of resources are available on the web to code and train a machine learning model. However…

The essential about fastText architecture, cleaning, upsampling and sentiments for tweets — In this post, we present fastText library, how it achieves faster speed and similar accuracy than some deep neural networks for text classification. Next, we show how to train a sentiment analysis model thanks to data generated with AWS Comprehend. …

We present a way to include bets p&l into a neural network classifier, using a custom loss function. — Sports betting is one of these perfect problems for machine learning algorithms and specifically classification neural networks. Tons of data available and a clear objective of picking the winner! Nonetheless, classic classification models are not well suited for betting strategies, and one needs to use a custom loss function in…

Since the start of the English Premier League season on 10 August 2018, fans all over the world have had numerous opportunities to express their support or anger toward teams and players on social media. Football fan’s typically react to the results of games, but also on the individual performance…