Deep Play-by-Play – labelling NBA plays using a 3D ConvNet
Labelling NBA action using deep learning :basketball: - GitHub - neeilan/DeepPlayByPlay: Labelling NBA action using deep learning
Deep Play-by-Play – labelling NBA plays using a 3D ConvNet launched on October 17, 2018 with 8 votes, #1,095 of 2,827 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 8 years on.
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A basketball hoop to maximize shots that go in [video]2020 · youtube.com · ▲971https://github.com/OlexG/finclaw ^ repo if anyone wants to contribute. I realized that sometimes I'm pretty good at making random guesses about the future. (I.E, I think OpenAI will beat Anthropic in the short term, etc...) However, I'm bad at converting these guesses into actual market plays I can profit from. As such, I wanted to make a tool that connects to the right APIs and launches a swarm of agent experts to generate related plays based on your prediction. The very first super shitty V0 MPV just has Polymarket/Kalshi bets, but I will be adding a more complex…
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