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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

We collaborate closely with enterprises to identify the prevalent challenges that hinder organizations from achieving their desired outcomes. Our designs aim to unlock possibilities that traditional methods have rendered impractical. Both large and small corporations need an AI platform that provides full empowerment and ownership. It is crucial to address data privacy while implementing AI solutions in a cost-effective manner. By improving operational efficiency, we enhance human work rather than replace it. Our application of AI allows for the automation of repetitive or hazardous tasks, minimizing the need for human involvement and accelerating processes with creativity and empathy. Machine Learning equips applications with seamless predictive capabilities, enabling the construction of classification and regression models. Additionally, it offers functionalities for clustering and visualizing different groupings. Supporting an array of ML libraries such as Weka, Scikit-Learn, H2O, and Tensorflow, it encompasses approximately 22 distinct algorithms tailored for developing classification, regression, and clustering models. This versatility ensures that businesses can adapt and thrive in a rapidly evolving technological landscape.

Description

The NVIDIA Deep Learning GPU Training System (DIGITS) empowers engineers and data scientists by making deep learning accessible and efficient. With DIGITS, users can swiftly train highly precise deep neural networks (DNNs) tailored for tasks like image classification, segmentation, and object detection. It streamlines essential deep learning processes, including data management, neural network design, multi-GPU training, real-time performance monitoring through advanced visualizations, and selecting optimal models for deployment from the results browser. The interactive nature of DIGITS allows data scientists to concentrate on model design and training instead of getting bogged down with programming and debugging. Users can train models interactively with TensorFlow while also visualizing the model architecture via TensorBoard. Furthermore, DIGITS supports the integration of custom plug-ins, facilitating the importation of specialized data formats such as DICOM, commonly utilized in medical imaging. This comprehensive approach ensures that engineers can maximize their productivity while leveraging advanced deep learning techniques.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Caffe No 
Dask No 
NetApp AIPod No 
TensorFlow No 
Torch No 
Unleash live No 

Integrations

Caffe Yes 
Dask Yes 
NetApp AIPod Yes 
TensorFlow Yes 
Torch Yes 
Unleash live Yes 

Pricing Details

No price information available.
Free Trial No 
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 Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Spotflock

Founded

2017

Country

India

Website

intellihub.ai/

Vendor Details

Company Name

NVIDIA DIGITS

Founded

1993

Country

United States

Website

developer.nvidia.com/digits

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 

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 
Weka Reviews

Weka

University of Waikato
ML.NET Reviews

ML.NET

Microsoft