Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Kraken caters to a wide range of users, from analysts to data scientists, by providing a user-friendly, no-code automated machine learning platform. It is designed to streamline and automate various data science processes, including data preparation, cleaning, algorithm selection, model training, and deployment. With a focus on making these tasks accessible, Kraken is particularly beneficial for analysts and engineers who may have some experience in data analysis. The platform’s intuitive, no-code interface and integrated SONAR© training empower users to evolve into citizen data scientists effortlessly. For data scientists, advanced functionalities enhance productivity and efficiency. Whether your routine involves using Excel or flat files for reporting or conducting ad-hoc analysis, Kraken simplifies the model-building process with features like drag-and-drop CSV uploads and an Amazon S3 connector. Additionally, the Data Connectors in Kraken enable seamless integration with various data warehouses, business intelligence tools, and cloud storage solutions, ensuring that users can work with their preferred data sources effortlessly. This versatility makes Kraken an indispensable tool for anyone looking to leverage machine learning without requiring extensive coding knowledge.
Description
SquareML is an innovative platform that eliminates the need for coding, making advanced data analytics and predictive modeling accessible to a wider audience, especially within the healthcare field. It empowers users with varying levels of technical ability to utilize machine learning tools without requiring in-depth programming skills. This platform excels in aggregating data from a range of sources, such as electronic health records, claims databases, medical devices, and health information exchanges. Among its standout features are a user-friendly data science lifecycle, generative AI models tailored for healthcare needs, the ability to convert unstructured data, a variety of machine learning models to forecast patient outcomes and disease advancement, and a collection of pre-existing models and algorithms. Additionally, it facilitates smooth integration with multiple healthcare data sources. By providing AI-driven insights, SquareML aims to simplify data workflows, elevate diagnostic precision, and ultimately enhance patient care outcomes, thereby fostering a healthier future for all.
API Access
Has API
No
API Access
Has API
No
Integrations
Amazon S3
Yes
Amazon Web Services (AWS)
No
Domo
Yes
Google Cloud BigQuery
Yes
Google Cloud Platform
No
Kryptos
Yes
Looker
Yes
Microsoft for Startups Founders Hub
No
MySQL
Yes
NVIDIA DRIVE
No
Integrations
Amazon S3
No
Amazon Web Services (AWS)
Yes
Domo
No
Google Cloud BigQuery
No
Google Cloud Platform
Yes
Kryptos
No
Looker
No
Microsoft for Startups Founders Hub
Yes
MySQL
No
NVIDIA DRIVE
Yes
Pricing Details
$100 per month
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Big Squid
Founded
2009
Country
United States
Website
www.bigsquid.com/kraken-platform
Vendor Details
Company Name
SquareML
Founded
2021
Country
United States
Website
www.squareml.ai/product
Product Features
Big Data
Collaboration
No
Data Blends
No
Data Cleansing
Yes
Data Mining
No
Data Visualization
Yes
Data Warehousing
No
High Volume Processing
No
No-Code Sandbox
No
Predictive Analytics
Yes
Templates
No
Machine Learning
Deep Learning
Yes
ML Algorithm Library
Yes
Model Training
Yes
Natural Language Processing (NLP)
No
Predictive Modeling
Yes
Statistical / Mathematical Tools
Yes
Templates
Yes
Visualization
Yes
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No