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Average Ratings 0 Ratings

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ease
features
design
support

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Description

ML Kit offers mobile developers access to Google's extensive machine learning capabilities in a streamlined and user-friendly format. By integrating ML Kit into your iOS and Android applications, you can enhance user engagement, personalization, and overall utility with solutions specifically designed to operate seamlessly on devices. The on-device processing ensures rapid performance and enables real-time applications, such as analyzing camera input. Furthermore, ML Kit functions offline, allowing for the secure processing of images and text that must stay on the device. This technology is built on the same machine learning models that support Google's mobile services, combining cutting-edge algorithms with sophisticated processing techniques through easily accessible APIs to facilitate impactful functionalities in your applications. Additionally, it can identify handwritten text and recognize hand-drawn shapes, including over 300 languages, emojis, and fundamental shapes. This versatility makes ML Kit an invaluable tool for developers looking to innovate and elevate their mobile offerings.

Description

Streamlining quality assurance for machine learning, Snitch cuts through the clutter to highlight the most valuable insights for enhancing your models. It allows you to monitor performance metrics that extend beyond mere accuracy through comprehensive dashboards and analytical tools. You can pinpoint issues within your data pipeline and recognize distribution changes before they impact your predictions. Once deployed, maintain your model in production while gaining insight into its performance and data throughout its lifecycle. Enjoy flexibility with your data security, whether in the cloud, on-premises, private cloud, or hybrid environments, while choosing your preferred installation method for Snitch. Seamlessly integrate Snitch into your existing MLops framework and continue using your favorite tools! Our installation process is designed for quick setup, ensuring that learning and operating the product are straightforward and efficient. Remember, accuracy alone can be deceptive; therefore, it’s crucial to assess your models for robustness and feature significance before launch. Obtain actionable insights that will help refine your models, and make comparisons with historical metrics and your models' established baselines to drive continuous improvement. This comprehensive approach not only bolsters performance but also fosters a deeper understanding of your machine learning processes.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)
Docker
Firebase
Google Cloud Platform
Microsoft Azure
TensorFlow

Integrations

Amazon Web Services (AWS)
Docker
Firebase
Google Cloud Platform
Microsoft Azure
TensorFlow

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$1,995 per year
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

Google

Founded

1998

Country

United States

Website

developers.google.com/ml-kit

Vendor Details

Company Name

Snitch AI

Country

Canada

Website

snit.ch/

Product Features

Machine Learning

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

Mobile App Development

Access Controls / Permissions
Any App Development Language
Collaboration Tools
Compatibility Testing
Data Modeling
Debugging
Drag and Drop Editor
Enterprise Mobility (EMM/MAM)
FaceID and TouchID
For Consumer Apps
For Enterprise Apps
Integration Options
Mobile App Security
Multi-Factor Authentication (MFA)
Multiple Apps from Same Base
No Dependencies
No-Code
Reporting / Analytics
Single Sign-On (SSO)
Source Control
Visual Editor

Product Features

Machine Learning

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

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