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About

Amazon SageMaker Model Training reduces the time and cost to train and tune machine learning (ML) models at scale without the need to manage infrastructure. You can take advantage of the highest-performing ML compute infrastructure currently available, and SageMaker can automatically scale infrastructure up or down, from one to thousands of GPUs. Since you pay only for what you use, you can manage your training costs more effectively. To train deep learning models faster, SageMaker distributed training libraries can automatically split large models and training datasets across AWS GPU instances, or you can use third-party libraries, such as DeepSpeed, Horovod, or Megatron. Efficiently manage system resources with a wide choice of GPUs and CPUs including P4d.24xl instances, which are the fastest training instances currently available in the cloud. Specify the location of data, indicate the type of SageMaker instances, and get started with a single click.

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. ​

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

Companies in need of a solution to train ML models quickly and cost effectively

Audience

Professional researchers and developers searching for a solution to manage their numerical computing and machine learning operations in Python

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Amazon
Founded: 1994
United States
aws.amazon.com/sagemaker/train/

Company Information

JAX
United States
docs.jax.dev/en/latest/

Alternatives

AWS Neuron

AWS Neuron

Amazon Web Services

Alternatives

Apache Mahout

Apache Mahout

Apache Software Foundation
AWS Neuron

AWS Neuron

Amazon Web Services
DeepSpeed

DeepSpeed

Microsoft
Gensim

Gensim

Radim Řehůřek

Categories

Categories

Integrations

Hugging Face
TensorFlow
Amazon SageMaker
Amazon Web Services (AWS)
BERT
CodeGPT
DALL·E 2
Equinox
Flower
Gemma 3n
Grain
Keras
LiteRT
NVIDIA NeMo Megatron
NumPy
PyTorch
Python

Integrations

Hugging Face
TensorFlow
Amazon SageMaker
Amazon Web Services (AWS)
BERT
CodeGPT
DALL·E 2
Equinox
Flower
Gemma 3n
Grain
Keras
LiteRT
NVIDIA NeMo Megatron
NumPy
PyTorch
Python
Claim Amazon SageMaker Model Training and update features and information
Claim Amazon SageMaker Model Training and update features and information
Claim JAX and update features and information
Claim JAX and update features and information