Python is the most popular programming language in the world. Its success lies in its versatility, allowing developers to create everything from simple APIs to complex applications. For machine learning and deep learning, Python has become a preferred language because of its flexibility. The data science and machine learning community has been developing many open source libraries for Python. GPUs are highly specialized chips designed to perform matrix multiplication operations at blazing speeds. Although they were initially intended for rendering computer graphics on screens, they have proved quite useful for machine learning applications as well. Python has a number of libraries that make it easy for us to leverage GPUs for both training and inference tasks. Some of these focus on improving generic performance by leveraging CUDA primitives and it provide higher level abstractions that allow you to quickly build complex architectures without worrying about implementation details. Some of the most popular open-source libraries for Python GPU among developers are: Jax - Composable transformations of Python NumPy programs; kitty - Cross platform, fast, feature rich, GPU based terminal; Image AI - python library built to empower developers to build applications.
Python 23518 Version:jax-v0.4.12 License: Permissive (Apache-2.0)
Python 7811 Version:test-resources-v3 License: Permissive (MIT)
Python 5166 Version:v1.3.0 License: Others (Non-SPDX)
Python 315 Version:v3.1 License: Permissive (Apache-2.0)
Python 249 Version:v3.1 License: Permissive (BSD-3-Clause)
Python 120 Version:Current License: Permissive (MIT)