F1 Race Predictions
Machine Learning Model created to predict F1 GP winners based on past performance, qualifying lap times, and historical F1 data.
This model utilizes FastF1 API for historical F1 data (race results, qualifying times, among other metrics) and Gradient Boosting model.
There are many future improvements that I would like to learn and add to this model.
Expected output example:
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🏁 Predicted GP Winner 🏁
Predicted Lap Times and GP Winner:
Abbreviation Q3_seconds Predicted_LapTime (s)
1 NOR 86.269 93.968200
2 ANT 86.271 93.968200
7 LEC 86.754 94.219445
0 VER 86.204 94.605306
Dracaena Marginata
Responsive web page about the Dragon Tree or most known as Dracaena Marginata. You will find some interesting facts and details on how to keep your little plant friend alive.
Tech stack: ReactJs, JavaScript, HTML/CSS/styled-components.
Check it here
Green Room
This webpage helps you to manage your plants based on few characteristics like, water, soil and light. Choose your own plants from the inventory, build and play around your Green Room.
Tech stack: Typescript, HTML, CSS, ReactJs, Postgres and ExpressJs.
Check it here
Toronto Gems
If you are new to the city of Toronto, don’t worry we got you covered! Besides the must go places this blog contains some underrated spots worth checking before they get popular (nobody likes big lines for IG shots right?).
Tech stack: MongoDB, ExpressJs, ReactJs, NodeJs, Javascript, HTML and CSS.
Check it here
Tripper
This app is perfect when you are going to a day trip or want to tour around the city. Feel free to create your own list of places, add them to your plan and visualize it on the map. Additionally, you can display the itinerary by clicking on the map icon.
