TobiasWhat is JAX?
JAX is Autograd and XLA, brought together for high-performance machine learning research. It automatically differentiates native Python and NumPy functions. It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives.
JAX is a tool in the Development & Training Tools category of a tech stack.
JAX Pros & Cons
Pros of JAX
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Cons of JAX
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JAX Alternatives & Comparisons
What are some alternatives to JAX?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
