Jenkins X

Jenkins X

The Linux Foundation

About

Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes. With SageMaker Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow (including data selection, cleansing, exploration, visualization, and processing at scale) from a single visual interface. You can use SQL to select the data you want from a wide variety of data sources and import it quickly. Next, you can use the Data Quality and Insights report to automatically verify data quality and detect anomalies, such as duplicate rows and target leakage. SageMaker Data Wrangler contains over 300 built-in data transformations so you can quickly transform data without writing any code. Once you have completed your data preparation workflow, you can scale it to your full datasets using SageMaker data processing jobs; train, tune, and deploy models.

About

Using Amazon SageMaker Pipelines, you can create ML workflows with an easy-to-use Python SDK, and then visualize and manage your workflow using Amazon SageMaker Studio. You can be more efficient and scale faster by storing and reusing the workflow steps you create in SageMaker Pipelines. You can also get started quickly with built-in templates to build, test, register, and deploy models so you can get started with CI/CD in your ML environment quickly. Many customers have hundreds of workflows, each with a different version of the same model. With the SageMaker Pipelines model registry, you can track these versions in a central repository where it is easy to choose the right model for deployment based on your business requirements. You can use SageMaker Studio to browse and discover models, or you can access them through the SageMaker Python SDK.

About

Amazon SageMaker Studio Lab is a free machine learning (ML) development environment that provides the compute, storage (up to 15GB), and security, all at no cost, for anyone to learn and experiment with ML. All you need to get started is a valid email address, you don’t need to configure infrastructure or manage identity and access or even sign up for an AWS account. SageMaker Studio Lab accelerates model building through GitHub integration, and it comes preconfigured with the most popular ML tools, frameworks, and libraries to get you started immediately. SageMaker Studio Lab automatically saves your work so you don’t need to restart in between sessions. It’s as easy as closing your laptop and coming back later. Free machine learning development environment that provides the computing, storage, and security to learn and experiment with ML. GitHub integration and preconfigured with the most popular ML tools, frameworks, and libraries so you can get started immediately.

About

Automate the continuous delivery of change through your environments via GitOps and create previews on pull requests to help you accelerate. Rather than having to have deep knowledge of Kubernetes, containers, or Tekton, Jenkins X will automate awesome Tekton pipelines for your projects that fully implement CI and CD which you can manage via GitOps. Each team gets a set of environments. Jenkins X then automates the management of the environments and the promotion of new versions of applications between environments via GitOps and pull requests. Jenkins X automatically spins up preview environments for your pull requests so you can get fast feedback before changes are merged to the main branch. Jenkins X automatically comments on your commits, issues, and pull requests with feedback as code is ready to be previewed, is promoted to environments, or if pull requests are generated automatically to upgrade versions.

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

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Professionals wanting a solution to select and understand data insights, and transform data to prepare it for ML

Audience

Individuals that need a first purpose-built CI/CD service for machine learning

Audience

Companies looking for a tool to learn and experiment with ML using a no-setup, free development environment

Audience

Teams and developers interested in a solution to accelerate their continuous delivery on Kubernetes

Support

Phone Support
24/7 Live Support
Online

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

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

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ease 0.0 / 5
features 0.0 / 5
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support 0.0 / 5

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Reviews/Ratings

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

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Reviews/Ratings

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

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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

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/data-wrangler/

Company Information

Amazon
Founded: 2006
United States
aws.amazon.com/sagemaker/pipelines/

Company Information

Amazon
Founded: 1994
United States
aws.amazon.com/sagemaker/studio-lab/

Company Information

The Linux Foundation
United States
jenkins-x.io

Alternatives

Alternatives

Alternatives

Alternatives

CodeNOW

CodeNOW

Stratox Cloud Native
Amazon SageMaker Ground Truth

Amazon SageMaker Ground Truth

Amazon Web Services
Argo CD

Argo CD

Applatix

Categories

Categories

Categories

Categories

Integrations

Amazon Athena
Amazon Redshift
Amazon S3
Amazon SageMaker Feature Store
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Apache Parquet
Conda
Databricks Data Intelligence Platform
Facebook Ads
Google Analytics
Google Cloud Tekton
JSON
Kubernetes
Mr Suricate
PySpark
SAP Cloud Platform
Salesforce
Snowflake
pandas

Integrations

Amazon Athena
Amazon Redshift
Amazon S3
Amazon SageMaker Feature Store
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Apache Parquet
Conda
Databricks Data Intelligence Platform
Facebook Ads
Google Analytics
Google Cloud Tekton
JSON
Kubernetes
Mr Suricate
PySpark
SAP Cloud Platform
Salesforce
Snowflake
pandas

Integrations

Amazon Athena
Amazon Redshift
Amazon S3
Amazon SageMaker Feature Store
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Apache Parquet
Conda
Databricks Data Intelligence Platform
Facebook Ads
Google Analytics
Google Cloud Tekton
JSON
Kubernetes
Mr Suricate
PySpark
SAP Cloud Platform
Salesforce
Snowflake
pandas

Integrations

Amazon Athena
Amazon Redshift
Amazon S3
Amazon SageMaker Feature Store
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Apache Parquet
Conda
Databricks Data Intelligence Platform
Facebook Ads
Google Analytics
Google Cloud Tekton
JSON
Kubernetes
Mr Suricate
PySpark
SAP Cloud Platform
Salesforce
Snowflake
pandas
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