Bifalgorithm post

If you watch the NBA and you're not building projects, you're wasting a huge opportunity to showcase your skills and your passions on your resume. And recruiters can smell the difference between a project that you built because you felt like you had to and a project that you built because you're passionate about it. So instead of just watching the playoffs, here are three interesting NBA projects you can build out this weekend. The first project is a Playoff Game Predictor Cyclocut Learn, Seaborn and Pandas. And the second project is a shock quality model. So you're going to use the exact same NBA Python package and you're going to get the shot location data. And you're going to get features like distance, defender distance, angle, shock clock and game situation. And using all of these features, you're going to train a gradient boosting model to predict if it would go in or would miss. And the tech stack that you need for this is the NBA VI, XGBoost, Pandas and Mapotlet. And for the third project and the coolest one on this list is a live win probability mod. For this project, you're going to get play by play logs of games from past seasons and you're going to get stats like the score difference, time left, possessions and files and you're going to use all of that to train a model. And what you'll be training is a neural network that outputs win percentage and what you're going to do with that is hook it up to a dashboard that updates in real time so you can show who's gonna win that game. The tech stack you need is the NBA API, Pandas, WebSocket, PyTorch and Flis. And if you want more projects like this, follow for more.

If you watch the NBA and you're not building projects, you're wasting a huge opportunity to showcase your skills and your passions on your resume. And recruite…