Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
You can develop on your laptop, then scale the same Python code elastically across hundreds or GPUs on any cloud. Ray converts existing Python concepts into the distributed setting, so any serial application can be easily parallelized with little code changes. With a strong ecosystem distributed libraries, scale compute-heavy machine learning workloads such as model serving, deep learning, and hyperparameter tuning. Scale existing workloads (e.g. Pytorch on Ray is easy to scale by using integrations. Ray Tune and Ray Serve native Ray libraries make it easier to scale the most complex machine learning workloads like hyperparameter tuning, deep learning models training, reinforcement learning, and training deep learning models. In just 10 lines of code, you can get started with distributed hyperparameter tune. Creating distributed apps is hard. Ray is an expert in distributed execution.
Description
DATAGYM empowers data scientists and machine learning professionals to annotate images at speeds that are ten times quicker than traditional methods. The use of AI-driven annotation tools minimizes the manual effort required, allowing for more time to refine machine learning models and enhancing the speed at which new products are launched. By streamlining data preparation, you can significantly boost the efficiency of your computer vision initiatives, reducing the time required by as much as half. This not only accelerates project timelines but also facilitates a more agile approach to innovation in the field.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Amazon EC2 Trn2 Instances
Yes
Amazon EKS
Yes
Amazon S3
No
Amazon Web Services (AWS)
Yes
Anyscale
Yes
Apache Airflow
Yes
Azure Kubernetes Service (AKS)
Yes
Dask
Yes
Databricks
Yes
Feast
Yes
Integrations
Amazon EC2 Trn2 Instances
No
Amazon EKS
No
Amazon S3
Yes
Amazon Web Services (AWS)
No
Anyscale
No
Apache Airflow
No
Azure Kubernetes Service (AKS)
No
Dask
No
Databricks
No
Feast
No
Pricing Details
Free
Open source. Consumption-based.
Free Trial
Yes
Free Version
Yes
Pricing Details
$19.00/month/user
Tiered Pricing Model with the Developer plan costing $0 a month.
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
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
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
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Anyscale
Founded
2019
Country
United States
Website
ray.io
Vendor Details
Company Name
eForce21
Founded
2019
Country
Germany
Website
www.datagym.ai/
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
Product Features
Data Analysis
Data Discovery
Yes
Data Visualization
Yes
High Volume Processing
Yes
Predictive Analytics
No
Regression Analysis
No
Sentiment Analysis
No
Statistical Modeling
No
Text Analytics
No
Data Management
Customer Data
No
Data Analysis
Yes
Data Capture
Yes
Data Integration
Yes
Data Migration
No
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
No
Data Visualization
Analytics
Yes
Content Management
Yes
Dashboard Creation
No
Filtered Views
No
OLAP
No
Relational Display
Yes
Simulation Models
No
Visual Discovery
Yes
Deep Learning
Convolutional Neural Networks
Yes
Document Classification
No
Image Segmentation
Yes
ML Algorithm Library
No
Model Training
Yes
Neural Network Modeling
Yes
Self-Learning
No
Visualization
Yes
Machine Learning
Deep Learning
Yes
ML Algorithm Library
No
Model Training
Yes
Natural Language Processing (NLP)
No
Predictive Modeling
Yes
Statistical / Mathematical Tools
No
Templates
No
Visualization
Yes