Eclipse Foundation Inc

Eclipse Deeplearning4j

7.8 /10

What is Eclipse Deeplearning4j?

Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs.

Company Details

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Eclipse Deeplearning4j Ratings

Real user data aggregated to summarize the product performance and customer experience.

86 Likeliness to Recommend

79 Plan to Renew

86 Satisfaction of Cost Relative to Value

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Emotional Footprint Overview

+99 Net Emotional Footprint

The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.

How much do users love Eclipse Deeplearning4j?

0% Negative

0% Neutral

100% Positive

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Feature Ratings

Average 85

Data Exploration and Visualization

Model Tuning

Performance and Scalability

Model Training

Data Pre-Processing

Algorithm Recommendation

Feature Engineering

Data Labeling

Pre-Packaged AI/ML Services

Data Ingestion

Ensembling

Vendor Capability Ratings

Average 83

Ease of Customization

Vendor Support

Ease of Implementation

Business Value Created

Quality of Features

Usability and Intuitiveness

Breadth of Features

Ease of Data Integration

Availability and Quality of Training

Product Strategy and Rate of Improvement

Ease of IT Administration

Eclipse Deeplearning4j Reviews

Ariel L.

Role: Sales Marketing
Industry: Other
Involvement: IT Development, Integration, and Administration

Validated Review

Verified Reviewer

Submitted Nov 2022

A development environment with excellent results

Likeliness to Recommend

8 /10

What differentiates Eclipse Deeplearning4j from other similar products?

It is used to develop web applications that are being used by our entire organization to visualize data. There are many business issues that we deal with in my organization. Users need to visualize data on their desktops.

What is your favorite aspect of this product?

The debugging experience is also very good. I recommend using a third-party library if you want to create a rich user interface for your software. An easy to use platform helps us save valuable time and effort as a group.

What do you dislike most about this product?

Eclipse has a wonderful user interface, but it feels a bit awkward, especially for newcomers. This is a minor flaw, but it still feels like it could be better. It overwhelms a bit to take the time to install and uninstall the application.

What recommendations would you give to someone considering this product?

Eclipse is ideal for a large enterprise. It has everything a person needs to code and, since it is a Microsoft product, it works very well with Windows. If you can't find something, there is a comprehensive search engine that searches for all Eclipse features.

Pros

Helps Innovate
Continually Improving Product
Performance Enhancing
Unique Features

Mahesh S.

Role: Consultant
Industry: Electronics
Involvement: Initial Implementation

Validated Review

Verified Reviewer

Submitted Jul 2021

This is fantastic anyone can use it

Likeliness to Recommend

8 /10

What differentiates Eclipse Deeplearning4j from other similar products?

Scalibility,productivity,easness,modular

What is your favorite aspect of this product?

Modularity

What do you dislike most about this product?

Size and service

What recommendations would you give to someone considering this product?

This is good product to solve lot of problems in bussines

Pros

Continually Improving Product
Caring
Helps Innovate
Performance Enhancing

Eclipse Deeplearning4j

What is Eclipse Deeplearning4j?

Company Details

Need Assistance?

Eclipse Deeplearning4j Ratings

86 Likeliness to Recommend

79 Plan to Renew

86 Satisfaction of Cost Relative to Value

Emotional Footprint Overview

+99 Net Emotional Footprint

How much do users love Eclipse Deeplearning4j?

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Data Exploration and Visualization Ability to visually manipulate, interact with, and explore data, and perform basic descriptive statistics and pattern detection.

Model Tuning 'Ability to fine-tune models based on monitoring feedback within the platform.

Performance and Scalability Systems performance (time) and scalability end-to-end: from data load and processing to model creation and deployment.

Model Training Ability to train a model with a range of data sets that you provide.

Data Pre-Processing Ability to wrangle or pre-process data to ready it for model training.

Algorithm Recommendation Ability to recommend a best ML algorithm to use based on dataset characteristics.

Feature Engineering Ability to extract and build features from raw data.

Data Labeling Ability to annotate/ label data to create a training data set.

Pre-Packaged AI/ML Services Pre-trained models and associated resources, e.g., for forecasting, recommendations, image and video analysis, NLP, voice, etc.

Data Ingestion Ability to access data from various sources on-prem and in the cloud and of various type: structured, unstructured, and semi-structured, real-time, etc.

Ensembling 'Ability to combine ML models for best results.

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Eclipse Deeplearning4j Reviews

Ariel L.

A development environment with excellent results

Likeliness to Recommend

Pros

Mahesh S.

This is fantastic anyone can use it

Likeliness to Recommend

Pros

Feature Ratings

Data Exploration and Visualization

Model Tuning

Performance and Scalability

Model Training

Data Pre-Processing

Algorithm Recommendation

Feature Engineering

Data Labeling

Pre-Packaged AI/ML Services

Data Ingestion

Ensembling

Vendor Capability Ratings

Ease of Customization

Vendor Support

Ease of Implementation

Business Value Created

Quality of Features

Usability and Intuitiveness

Breadth of Features

Ease of Data Integration

Availability and Quality of Training

Product Strategy and Rate of Improvement

Ease of IT Administration