facet
Human-explainable AI. (by BCG-Gamma)
NBA-attendance-prediction
Attendance prediction tool for NBA games using machine learning. Full pipeline implemented in Python from data ingestion to prediction. Attained mean absolute error of around 800 people (about 5% capacity) on test set. (by wyattowalsh)
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| facet | NBA-attendance-prediction | |
|---|---|---|
| 5 | 1 | |
| 471 | 9 | |
| - | - | |
| 5.6 | 0.0 | |
| 9 months ago | about 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
facet
Posts with mentions or reviews of facet.
We have used some of these posts to build our list of alternatives
and similar projects.
-
/r/technology top posts: Mar 1, 2021
FACET is an open source library for human-explainable AI. It combines sophisticated model inspection and model-based simulation to enable better explanations of your supervised machine learning models.\ (0 comments)
- FACET is an open source library for human-explainable AI. It combines sophisticated model inspection and model-based simulation to enable better explanations of your supervised machine learning models.
- Human-Explainable AI
- Facet: ML model inspection and model-based simulation for better explanations
NBA-attendance-prediction
Posts with mentions or reviews of NBA-attendance-prediction.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-04-06.
-
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 👍
What are some alternatives?
When comparing facet and NBA-attendance-prediction you can also consider the following projects:
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
nba_api - An API Client package to access the APIs for NBA.com
transient_rotordynamic - transient dynamics of elastic rotors in journal bearings with Julia and Python
Basketball_Analytics - Repository which contains various scripts and work with various basketball statistics