With Bahrain Grand Prix approaching, here are my predictions for both qualifying and race. For the first time this year, the Mercedes drivers are expected to fill-up the front-row with Raikkonen starting 5th despite his phenomenal performance there last year. Race predictions will be updated after the qualifying.
Here are my predictions for the upcoming Chinese Grand Prix. After an impressive win in Albert Park, Vettel is the algorithm’s favourite to take the pole position with Hamilton filling up the front row. Surprisingly, Bottas is predicted to start fifth. Race predictions have been updated after the qualifying.
After discussing in my previous post about Data Acquisition, here I’m going to describe the most important part of any Machine Learning pipeline i.e. Feature Engineering.
Having defined what we are trying to achieve, it’s time to start thinking about what data we need and how we are going to obtain them in order to create features and train our models.
Hereby I present you with the first predictions made by the algorithm. The model has not seen any data from the recent testing in Barcelona so everything is based on the drivers’ and teams’ performance in the past years. I expect the accuracy of the predictions to increase as the season progresses. Race predictions have been updated after the qualifying.
In this series of posts I’m going to explain the process behind building a Machine-Learning model capable of predicting F1 race outcomes. This is not intented to be a complete guide so some background on building ML pipelines is assumed.
Welcome to F1 predictor, a blog in the crossroads of my two passions: Formula 1 and Data Science. If you are passionate about any of the above, I’m sure you’ll find something interesting in here!