Julia vs Numba
Overview
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CLI (Node.js)
Manual
Detailed Comparison
Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. | It translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. It offers a range of options for parallelising Python code for CPUs and GPUs, often with only minor code changes. |
| - | On-the-fly code generation;
Native code generation for the CPU (default) and GPU hardware;
Integration with the Python scientific software stack |
Statistics | |
GitHub Stars 47.9K | GitHub Stars 0 |
GitHub Forks 5.7K | GitHub Forks 0 |
Stacks 666 | Stacks 20 |
Followers 677 | Followers 44 |
Votes 171 | Votes 0 |
Pros & Cons | |
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Cons
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Integrations | |
What are some alternatives to Julia, Numba?
Meteor
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Bower
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Elm
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TensorFlow
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Racket
It is a general-purpose, multi-paradigm programming language based on the Scheme dialect of Lisp. It is designed to be a platform for programming language design and implementation. It is also used for scripting, computer science education, and research.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
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.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
Kubeflow
The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.
TensorFlow.js
Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API
