Related Products
|
||||||
About
JAX is a Python library designed for high-performance numerical computing and machine learning research. It offers a NumPy-like API, facilitating seamless adoption for those familiar with NumPy. Key features of JAX include automatic differentiation, just-in-time compilation, vectorization, and parallelization, all optimized for execution on CPUs, GPUs, and TPUs. These capabilities enable efficient computation for complex mathematical functions and large-scale machine-learning models. JAX also integrates with various libraries within its ecosystem, such as Flax for neural networks and Optax for optimization tasks. Comprehensive documentation, including tutorials and user guides, is available to assist users in leveraging JAX's full potential.
|
About
Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.
|
About
Scikit-learn provides simple and efficient tools for predictive data analysis. Scikit-learn is a robust, open source machine learning library for the Python programming language, designed to provide simple and efficient tools for data analysis and modeling. Built on the foundations of popular scientific libraries like NumPy, SciPy, and Matplotlib, scikit-learn offers a wide range of supervised and unsupervised learning algorithms, making it an essential toolkit for data scientists, machine learning engineers, and researchers. The library is organized into a consistent and flexible framework, where various components can be combined and customized to suit specific needs. This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.
|
||||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
||||
Audience
Professional researchers and developers searching for a solution to manage their numerical computing and machine learning operations in Python
|
Audience
Component Library solution for DevOps teams
|
Audience
Engineers and data scientists requiring a solution to manage and improve their machine learning research
|
||||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
||||
API
Offers API
|
API
Offers API
|
API
Offers API
|
||||
Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
||||
Pricing
No information available.
Free Version
Free Trial
|
Pricing
Free
Free Version
Free Trial
|
Pricing
Free
Free Version
Free Trial
|
||||
Reviews/
|
Reviews/
|
Reviews/
|
||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
||||
Company InformationJAX
United States
docs.jax.dev/en/latest/
|
Company InformationNumPy
numpy.org
|
Company Informationscikit-learn
United States
scikit-learn.org/stable/
|
||||
Alternatives |
Alternatives |
Alternatives |
||||
|
|
|
|||||
|
|
|
|||||
|
|
||||||
|
|
|
|||||
Categories |
Categories |
Categories |
||||
Integrations
Flower
3LC
Avanzai
Databricks Data Intelligence Platform
Equinox
Guild AI
Hugging Face
Intel Tiber AI Studio
JAX
LiteRT
|
Integrations
Flower
3LC
Avanzai
Databricks Data Intelligence Platform
Equinox
Guild AI
Hugging Face
Intel Tiber AI Studio
JAX
LiteRT
|
Integrations
Flower
3LC
Avanzai
Databricks Data Intelligence Platform
Equinox
Guild AI
Hugging Face
Intel Tiber AI Studio
JAX
LiteRT
|
||||
|
|
|
|