get-started-with-JAX VS awesome-jax

Compare get-started-with-JAX vs awesome-jax and see what are their differences.

get-started-with-JAX

The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem. (by gordicaleksa)

awesome-jax

JAX - A curated list of resources https://github.com/google/jax (by n2cholas)
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get-started-with-JAX awesome-jax
3 3
558 1,288
- -
0.0 6.2
5 months ago 11 days ago
Jupyter Notebook
MIT License Creative Commons Zero v1.0 Universal
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.

get-started-with-JAX

Posts with mentions or reviews of get-started-with-JAX. We have used some of these posts to build our list of alternatives and similar projects.

awesome-jax

Posts with mentions or reviews of awesome-jax. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-29.

What are some alternatives?

When comparing get-started-with-JAX and awesome-jax you can also consider the following projects:

Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.

awesome-production-machine-learning - A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

awesome-ocr

Human-pose-estimation - A quick tutorial on multi-pose estimation with OpenCV, Tensorflow and MoveNet lightning.

awesome-ai-in-finance - 🔬 A curated list of awesome LLMs & deep learning strategies & tools in financial market.

JustEnoughScalaForSpark - A tutorial on the most important features and idioms of Scala that you need to use Spark's Scala APIs.

equinox - Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/

TF_JAX_tutorials - All about the fundamental blocks of TF and JAX!

awesome-deep-learning - A curated list of awesome Deep Learning tutorials, projects and communities.

tensor-sensor - The goal of this library is to generate more helpful exception messages for matrix algebra expressions for numpy, pytorch, jax, tensorflow, keras, fastai.

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration