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About

Attempting to build Machine Learning Pipelines internally often takes longer and costs more than planned. And worse, Gartner shows that more than 80% of AI Projects will fail. With Cortex, we help teams get up and running with machine learning faster and cheaper than alternatives, all while putting data to use to improve business outcomes. Empower every team with the ability to create their own AI Predictions. No longer will you need to wait to hire a team and build out costly infrastructure. With Cortex you can create predictions from the data you already have, all through an easy to use web interface. Now everyone is a Data Scientist! Cortex automates the process of turning raw data into Machine Learning Pipelines, eliminating the hardest and most time consuming aspects of AI. These predictions stay accurate and up to date by continuously ingesting new data and updating the underlying model automatically – no human intervention needed.

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
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Business teams looking for no code AI

Audience

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

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

Free
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:

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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

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

Vidora
Founded: 2013
United States
vidora.com

Company Information

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

Alternatives

OnPoint CORTEX

OnPoint CORTEX

OnPoint - A Koch Engineered Solutions Company

Alternatives

Gensim

Gensim

Radim Řehůřek
ML.NET

ML.NET

Microsoft
MLlib

MLlib

Apache Software Foundation
Keepsake

Keepsake

Replicate

Categories

Categories

Integrations

Adobe Analytics
Amazon Web Services (AWS)
Ascend
DagsHub
Flower
GLM-5.1
Google Cloud Platform
MLJAR Studio
Matplotlib
Microsoft Azure
MoEngage
ModelOp
NumPy
Python
Salesforce
Snowflake
Tableau
Train in Data

Integrations

Adobe Analytics
Amazon Web Services (AWS)
Ascend
DagsHub
Flower
GLM-5.1
Google Cloud Platform
MLJAR Studio
Matplotlib
Microsoft Azure
MoEngage
ModelOp
NumPy
Python
Salesforce
Snowflake
Tableau
Train in Data
Claim Vidora Cortex and update features and information
Claim Vidora Cortex and update features and information
Claim scikit-learn and update features and information
Claim scikit-learn and update features and information