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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

GitLens reveals the hidden insights within every repository, enhancing the visualization of code authorship through the use of CodeLens and Git blame, which provide a detailed history for each line of code. Effortlessly navigate and investigate Git repositories, extracting meaningful insights with robust comparison commands, all while maintaining a smooth development workflow. Although GitLens is packed with features, it offers extensive customization options to fit your individual preferences — if you find the code lens distracting or the line blame annotations cumbersome, you can easily disable them or adjust their settings. At the end of every line, an unobtrusive annotation displays the last commit and author who modified that line, allowing for quick reference. Additionally, the status bar provides similar blame information, further enriching your coding experience. This level of detail not only enhances collaboration among team members but also promotes accountability in code contributions.

Description

MLflow is an open-source suite designed to oversee the machine learning lifecycle, encompassing aspects such as experimentation, reproducibility, deployment, and a centralized model registry. The platform features four main components that facilitate various tasks: tracking and querying experiments encompassing code, data, configurations, and outcomes; packaging data science code to ensure reproducibility across multiple platforms; deploying machine learning models across various serving environments; and storing, annotating, discovering, and managing models in a unified repository. Among these, the MLflow Tracking component provides both an API and a user interface for logging essential aspects like parameters, code versions, metrics, and output files generated during the execution of machine learning tasks, enabling later visualization of results. It allows for logging and querying experiments through several interfaces, including Python, REST, R API, and Java API. Furthermore, an MLflow Project is a structured format for organizing data science code, ensuring it can be reused and reproduced easily, with a focus on established conventions. Additionally, the Projects component comes equipped with an API and command-line tools specifically designed for executing these projects effectively. Overall, MLflow streamlines the management of machine learning workflows, making it easier for teams to collaborate and iterate on their models.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Axolotl
Azure Data Science Virtual Machines
Azure Machine Learning
Azure Marketplace
Cranium
Determined AI
Docker
Git
H2O.ai
IBM watsonx.data integration
Kedro
Keras
Ragas
Robust Intelligence
Superwise
TensorFlow
Union Cloud
Unity Catalog
Vectice
Visual Studio Code

Integrations

Axolotl
Azure Data Science Virtual Machines
Azure Machine Learning
Azure Marketplace
Cranium
Determined AI
Docker
Git
H2O.ai
IBM watsonx.data integration
Kedro
Keras
Ragas
Robust Intelligence
Superwise
TensorFlow
Union Cloud
Unity Catalog
Vectice
Visual Studio Code

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

GitKraken

Country

United States

Website

www.gitkraken.com/gitlens

Vendor Details

Company Name

MLflow

Founded

2018

Country

United States

Website

mlflow.org

Product Features

Application Development

Access Controls/Permissions
Code Assistance
Code Refactoring
Collaboration Tools
Compatibility Testing
Data Modeling
Debugging
Deployment Management
Graphical User Interface
Mobile Development
No-Code
Reporting/Analytics
Software Development
Source Control
Testing Management
Version Control
Web App Development

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Alternatives

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