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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

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 Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

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

Audience

Engineers and data scientists requiring a solution to manage and improve their machine learning research

Support

Phone Support Not Supported
24/7 Live Support Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

Free
Free Version Supported
Free Trial Not Supported

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 Supported
Webinars Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

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

Company Information

scikit-learn
United States
scikit-learn.org/stable/

Alternatives

Alternatives

Gensim

Gensim

Radim Řehůřek
ML.NET

ML.NET

Microsoft
MLlib

MLlib

Apache Software Foundation
Keepsake

Keepsake

Replicate

Categories

Categories

Machine Learning Supported

Integrations

Amazon SageMaker Supported
Amazon Web Services (AWS) Supported
BERT Supported
DALL·E 2 Supported
DagsHub Not Supported
Databricks Not Supported
Flower Not Supported
GLM-5.1 Not Supported
GLM-5.2 Not Supported
GLM-5.3 Not Supported
Guild AI Not Supported
Hugging Face Supported
MLJAR Studio Not Supported
Matplotlib Not Supported
ModelOp Not Supported
NVIDIA NeMo Megatron Supported
NumPy Not Supported
TensorFlow Supported
Thunder Compute Not Supported

Integrations

Amazon SageMaker Not Supported
Amazon Web Services (AWS) Not Supported
BERT Not Supported
DALL·E 2 Not Supported
DagsHub Supported
Databricks Supported
Flower Supported
GLM-5.1 Supported
GLM-5.2 Supported
GLM-5.3 Supported
Guild AI Supported
Hugging Face Not Supported
MLJAR Studio Supported
Matplotlib Supported
ModelOp Supported
NVIDIA NeMo Megatron Not Supported
NumPy Supported
TensorFlow Not Supported
Thunder Compute Supported
Claim Amazon SageMaker Model Training and update features and information
Claim Amazon SageMaker Model Training and update features and information
Claim scikit-learn and update features and information
Claim scikit-learn and update features and information