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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

The SensiML Analytics Toolkit enables the swift development of smart IoT sensor devices while simplifying the complexities of data science. It focuses on creating compact algorithms designed to run on small IoT endpoints instead of relying on cloud processing. By gathering precise, traceable, and version-controlled datasets, it enhances data integrity. The toolkit employs advanced AutoML code generation to facilitate the rapid creation of autonomous device code. Users can select their preferred interface and level of AI expertise while maintaining full oversight of all algorithm components. It also supports the development of edge tuning models that adapt behavior based on incoming data over time. The SensiML Analytics Toolkit automates every step necessary for crafting optimized AI recognition code for IoT sensors. Utilizing an expanding library of sophisticated machine learning and AI algorithms, the overall workflow produces code capable of learning from new data, whether during development or after deployment. Moreover, non-invasive applications for rapid disease screening that intelligently classify multiple bio-sensing inputs serve as essential tools for aiding healthcare decision-making processes. This capability positions the toolkit as an invaluable resource in both tech and healthcare sectors.

Description

We have created a deep learning algorithm inspired by neuro-biology that functions similarly to an intelligence assessment. This innovative tool autonomously identifies and forecasts patterns, enabling the effortless construction of smart applications. Our user-friendly software features a clear and concise REST API, making it possible to develop intelligent applications across various environments. Consequently, you can seamlessly integrate it with JavaScript applications, spreadsheets, and even your online trading platforms. For development and testing purposes, our service is completely free to use. The community edition is available as open-source under the SSPL license. The Vanillatech ML Workstation provides ready-to-use software that operates on your local computer. Should you need any modifications or additional support, please reach out to us for a customized proposal tailored to your needs. With our commitment to accessibility and support, we aim to empower developers at every skill level.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS Marketplace No 

Integrations

AWS Marketplace Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App Yes 
Windows Yes 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App Yes 
iPad App Yes 
Android App Yes 
Windows Yes 
Mac Yes 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

SensiML

Founded

2017

Country

United States

Website

sensiml.com

Vendor Details

Company Name

Vanillatech

Founded

2018

Country

Germany

Website

timeseriesforecasting.com

Product Features

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 Yes 
ML Algorithm Library Yes 
Model Training Yes 
Natural Language Processing (NLP) No 
Predictive Modeling Yes 
Statistical / Mathematical Tools Yes 
Templates No 
Visualization No 

Alternatives

Alternatives