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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Kedro serves as a robust framework for establishing clean data science practices. By integrating principles from software engineering, it enhances the efficiency of machine-learning initiatives. Within a Kedro project, you will find a structured approach to managing intricate data workflows and machine-learning pipelines. This allows you to minimize the time spent on cumbersome implementation tasks and concentrate on addressing innovative challenges. Kedro also standardizes the creation of data science code, fostering effective collaboration among team members in problem-solving endeavors. Transitioning smoothly from development to production becomes effortless with exploratory code that can evolve into reproducible, maintainable, and modular experiments. Additionally, Kedro features a set of lightweight data connectors designed to facilitate the saving and loading of data across various file formats and storage systems, making data management more versatile and user-friendly. Ultimately, this framework empowers data scientists to work more effectively and with greater confidence in their projects.

Description

Data science projects achieve success when data scientists possess the ability to independently create, enhance, and manage comprehensive workflows while prioritizing their data science tasks over engineering concerns. By utilizing Metaflow alongside popular data science libraries like TensorFlow or SciKit Learn, you can write your models in straightforward Python syntax without needing to learn much that is new. Additionally, Metaflow supports the R programming language, broadening its usability. This tool aids in designing workflows, scaling them effectively, and deploying them into production environments. It automatically versions and tracks all experiments and data, facilitating easy inspection of results within notebooks. With tutorials included, newcomers can quickly familiarize themselves with the platform. You even have the option to duplicate all tutorials right into your current directory using the Metaflow command line interface, making it a seamless process to get started and explore further. As a result, Metaflow not only simplifies complex tasks but also empowers data scientists to focus on impactful analyses.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker
Apache Airflow
Apache Spark
Azure Databricks
Azure Machine Learning
Comet LLM
Dask
Docker
Jupyter Notebook
Kubeflow
MLflow
Matplotlib
Outerbounds
Plotly Dash
Python
Superwise
Vertex AI
pandas

Integrations

Amazon SageMaker
Apache Airflow
Apache Spark
Azure Databricks
Azure Machine Learning
Comet LLM
Dask
Docker
Jupyter Notebook
Kubeflow
MLflow
Matplotlib
Outerbounds
Plotly Dash
Python
Superwise
Vertex AI
pandas

Pricing Details

Free
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

Kedro

Website

kedro.org

Vendor Details

Company Name

Metaflow

Website

metaflow.org

Product Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Product Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

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Alternatives

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