nba-stats-analysis VS fastai

Compare nba-stats-analysis vs fastai and see what are their differences.

nba-stats-analysis

Jupyter Notebooks with Applications of Data Science and Analysis with NBA data, using the information available through the NBA Stats API. (by lbiedma)
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nba-stats-analysis fastai
1 9
2 25,638
- 0.6%
2.7 8.0
almost 3 years ago 8 days 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.

nba-stats-analysis

Posts with mentions or reviews of nba-stats-analysis. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-07-30.
  • Weekly Friday Self-Promotion and Fan Art Thread
    2 projects | /r/nba | 30 Jul 2021
    I have been using it to make some analytics job on a couple of different points, as I start reading sources like Dean Oliver's Basketball on Paper, and have been uploading it to my GitHub repo. The format is in Jupyter Notebooks, so if anyone is familiar with Python, you can run it on your own computers.

fastai

Posts with mentions or reviews of fastai. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-04.

What are some alternatives?

When comparing nba-stats-analysis and fastai you can also consider the following projects:

nba_api - An API Client package to access the APIs for NBA.com

pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]

homemade-machine-learning - 🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

fastbook - The fastai book, published as Jupyter Notebooks

Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.

Watermark-Removal-Pytorch - 🔥 CNN for Watermark Removal using Deep Image Prior with Pytorch 🔥.

TensorFlow-Examples - TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

PySyft - Perform data science on data that remains in someone else's server

lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)

ru-dalle - Generate images from texts. In Russian

pytorch-lightning - Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

iterative-grabcut - This algorithm uses a rectangle made by the user to identify the foreground item. Then, the user can edit to add or remove objects to the foreground. Then, it removes the background and makes it transparent.