NBA-attendance-prediction
ML-Workspace
NBA-attendance-prediction | ML-Workspace | |
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1 | 7 | |
9 | 3,324 | |
- | 0.4% | |
0.0 | 2.7 | |
about 1 year ago | 6 months ago | |
Jupyter Notebook | Jupyter Notebook | |
- | Apache License 2.0 |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
NBA-attendance-prediction
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New NBA dataset on Kaggle! - Every game 60,000+ (1946-2021) w/ box scores, line scores, series info, and more - every player 4500+ w/ draft data, career stats, biometrics, and more - and every team (30 w/ franchise histories, coaches/staffing, and more). Updated daily, with plans for expansion!
The current iteration contains attendance numbers through the Box Scores within the Game table. It's actually funny you ask about that particular feature; that was my inspiration for creating the dataset in general. I had previously scraped data from basketball-reference.com to use in order to create an attendance prediction tool for NBA stadium organization leaders and struggled to find reliable, robust data. However, via stats.nba.com, the attendance data is rather solid 👍
ML-Workspace
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[D] I recently quit my job to start a ML company. Would really appreciate feedback on what we're working on.
Also check out: https://github.com/ml-tooling/ml-workspace, it a nice open source project with lots of packages ready to use.
- ML-Workspace
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Coding for machine learning on Tab S8?
The other option - no reason why you couldn't host something on the desktop machine - web based IDE like R-Studio or Python - have a look at ml-workspace - https://github.com/ml-tooling/ml-workspace that runs in Docker and would provide interfaces for both Python and R, VSCode as well as a GPU accelerated variant for doing Tensorflow etc - either Windows or Linux can support Docker containers (Linux is less trouble apparently - I only have played with it in Linux personally)
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Dynamically spin up VM (based on specific HTTPS request) and stop it once session is over?
It will be a web based IDE dev kit (like Jupyter Hub, or JupyterLab) if you are familiar with them)
- All-in-One Docker Based IDE for Data Science and ML
- Visual Studio Code now available as Web based editor for GitHub repos
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[P] Install or update CUDA, NVIDIA Drivers, Pytorch, Tensorflow, and CuDNN with a single command: Lambda Stack
I'll stick with https://github.com/ml-tooling/ml-workspace, is a docker with all tools installed, also the option of using GPU, so I think is better than only for debian. This way anyone can use it.
What are some alternatives?
nba_api - An API Client package to access the APIs for NBA.com
JupyterLab - JupyterLab computational environment.
Basketball_Analytics - Repository which contains various scripts and work with various basketball statistics
Gitpod - DEPRECATED since Gitpod 0.5.0; use https://github.com/gitpod-io/gitpod/tree/master/chart and https://github.com/gitpod-io/gitpod/tree/master/install/helm
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
keytotext - Keywords to Sentences
sports-analytics - Data collection, processing, visualization, modeling, and ideation in the space of sports analytics
self-hosted - Sentry, feature-complete and packaged up for low-volume deployments and proofs-of-concept
SQL-for-Data-Analytics - Perform fast and efficient data analysis with the power of SQL
Code-Server - VS Code in the browser
datadoubleconfirm - Simple datasets and notebooks for data visualization, statistical analysis and modelling - with write-ups here: http://projectosyo.wix.com/datadoubleconfirm.
cocalc-docker - DEPRECATED (was -- Docker setup for running CoCalc as downloadable software on your own computer)