Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Cloud AutoML represents a collection of machine learning tools that allow developers with minimal expertise in the field to create tailored models that meet their specific business requirements. This technology harnesses Google's advanced transfer learning and neural architecture search methodologies. By utilizing over a decade of exclusive research advancements from Google, Cloud AutoML enables your machine learning models to achieve enhanced accuracy and quicker performance. With its user-friendly graphical interface, you can effortlessly train, assess, refine, and launch models using your own data. In just a few minutes, you can develop a personalized machine learning model. Additionally, Google’s human labeling service offers a dedicated team to assist in annotating or refining your data labels, ensuring that your models are trained on top-notch data for optimal results. This combination of advanced technology and user support makes Cloud AutoML an accessible option for businesses looking to leverage machine learning.
Description
Produvia offers a serverless machine learning development service that streamlines the creation and deployment of machine learning models through advanced cloud infrastructure. By collaborating with Produvia, businesses can leverage this cutting-edge technology to innovate and implement their machine learning strategies effectively. Renowned Fortune 500 companies and Global 500 enterprises turn to Produvia for assistance in building and launching machine learning models utilizing contemporary cloud solutions. At Produvia, we harness the latest advancements in machine learning and deep learning to address various business challenges. Many organizations find themselves spending excessively on infrastructure, prompting a shift toward serverless architectures that help mitigate server-related expenses. The complexity of outdated servers and legacy systems often hampers progress, which has led modern companies to adopt machine learning technologies aimed at transforming their technology frameworks. While many businesses typically hire software developers to create traditional code, innovative organizations are now employing machine learning to produce software capable of generating code autonomously. As the landscape of technology evolves, the shift to automated software development is becoming increasingly prevalent.
API Access
Has API
No
API Access
Has API
No
Integrations
ASPIRE Health
Yes
AWS Marketplace
Yes
Amazon SageMaker Model Building
Yes
Axon Ivy
Yes
B2Metric
Yes
Beats
Yes
Dataiku
Yes
Elastic Observability
Yes
Evoltsoft
Yes
Google Cloud Healthcare API
Yes
Integrations
ASPIRE Health
No
AWS Marketplace
No
Amazon SageMaker Model Building
No
Axon Ivy
No
B2Metric
No
Beats
No
Dataiku
No
Elastic Observability
No
Evoltsoft
No
Google Cloud Healthcare API
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
$1,000 per month
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
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Founded
1998
Country
United States
Website
cloud.google.com/automl
Vendor Details
Company Name
Produvia
Founded
2013
Country
Canada
Website
produvia.com
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
Product Features
Deep Learning
Convolutional Neural Networks
No
Document Classification
No
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
No
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