Eclipse Foundation Inc

Eclipse Deeplearning4j

Composite Score

7.8 /10

CX Score

8.0 /10

13 Reviews Write a Review

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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.

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Eclipse Deeplearning4j Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on Eclipse Deeplearning4j.

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

89 Likeliness to Recommend

2
Since last award

87 Plan to Renew

6
Since last award

87 Satisfaction of Cost Relative to Value

1
Since last award

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Emotional Footprint Overview

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

+96 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 82

Performance and Scalability

Data Pre-Processing

Model Tuning

Openness and Flexibility

Data Exploration and Visualization

Feature Engineering

Data Ingestion

Pre-Packaged AI/ML Services

Ensembling

Model Training

Algorithm Recommendation

Vendor Capability Ratings

Average 82

Ease of Customization

Quality of Features

Vendor Support

Business Value Created

Breadth of Features

Usability and Intuitiveness

Availability and Quality of Training

Ease of Implementation

Ease of Data Integration

Product Strategy and Rate of Improvement

Ease of IT Administration

Eclipse Deeplearning4j Reviews

Syed A.

Role: Operations
Industry: Telecommunications
Involvement: Business Leader or Manager

Validated Review

Verified Reviewer

Submitted Nov 2024

Easy to use, but a bit pricey

Likeliness to Recommend

9 /10

What differentiates Eclipse Deeplearning4j from other similar products?

what sets Eclipse Deeplearning4j apart is its deep integration with the Java ecosystem. It’s built for scalability, fits right into enterprise systems, and supports large-scale applications. It’s open-source, efficient, and perfect for those already using Java.

What is your favorite aspect of this product?

my favorite part of Eclipse Deeplearning4j is its seamless integration with Java. It’s reliable, scalable, and perfect for enterprises already in that ecosystem. It’s open-source, too—helping communities innovate, while providing the stability businesses need to grow.

What do you dislike most about this product?

what I don’t love about Eclipse Deeplearning4j is that it’s a bit limiting if you’re not in the Java ecosystem. It can be tough for folks coming from Python or other languages, and it lacks some advanced features.

What recommendations would you give to someone considering this product?

if you’re already deep in the Java ecosystem, Eclipse Deeplearning4j is a great choice—it’s scalable, reliable, and integrates well with big data tools. But if you’re coming from Python or need advanced features, consider other options too.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Kumar A.

Role: Information Technology
Industry: Engineering
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Mar 2024

Awesome Product

Likeliness to Recommend

9 /10

What differentiates Eclipse Deeplearning4j from other similar products?

Eclipse Deeplearning4j's unique Java-based architecture offers seamless integration with existing enterprise systems and extensive support for distributed computing, setting it apart from other frameworks.

What is your favorite aspect of this product?

appreciate Eclipse Deeplearning4j's robust Java-based architecture and its extensive support for distributed computing.

What do you dislike most about this product?

i have no dislike

What recommendations would you give to someone considering this product?

I would recommend exploring Eclipse Deeplearning4j for its strong Java-based architecture, extensive support for distributed computing, and active community, ensuring comprehensive resources and scalability for deep learning projects.

Pros

Helps Innovate
Reliable
Performance Enhancing
Enables Productivity

Vaibhav K.

Role: Consultant
Industry: Technology
Involvement: IT Development, Integration, and Administration

Validated Review

Verified Reviewer

Submitted Jan 2024

Best Partner For Developers

Likeliness to Recommend

9 /10

What differentiates Eclipse Deeplearning4j from other similar products?

When we are dealing with the data and we want to anylyze it and come to final conclusion then we need a tool so then the Eclipse Deeplearning4j comes in the picture. Also it has the intelligence that if you make something typo then it prompt the correct text that means it has the best debugging feature which correct the code. The capability if the product are limited for the developers .

What is your favorite aspect of this product?

It has very good interface and easy to use also it is vey much light in the computing resources like RAM, CPU.

What do you dislike most about this product?

Has some issue when we load a large file otherwise rest of the things are good.

What recommendations would you give to someone considering this product?

Best product when your requirement matches surely go for it. Also you dont want to switch from this env because it has multi language support.

Pros

Reliable
Caring
Respectful
Client's Interest First

Eclipse Deeplearning4j

What is Eclipse Deeplearning4j?

Company Details

Need Assistance?

Eclipse Deeplearning4j Ratings

89 Likeliness to Recommend

2 Since last award

87 Plan to Renew

6 Since last award

87 Satisfaction of Cost Relative to Value

1 Since last award

Emotional Footprint Overview

+96 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

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

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

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

Openness and Flexibility Integration with open-source and 3P resources (languages, frameworks, libraries, etc.)

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

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

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.

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

Ensembling 'Ability to combine ML models for best results.

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

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

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.

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.

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.

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.

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.

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.

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.

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.

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

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

Syed A.

Easy to use, but a bit pricey

Likeliness to Recommend

Pros

Kumar A.

Awesome Product

Likeliness to Recommend

Pros

Vaibhav K.

Best Partner For Developers

Likeliness to Recommend

Pros

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Feature Ratings

Performance and Scalability

Data Pre-Processing

Model Tuning

Openness and Flexibility

Data Exploration and Visualization

Feature Engineering

Data Ingestion

Pre-Packaged AI/ML Services

Ensembling

Model Training

Algorithm Recommendation

Vendor Capability Ratings

Ease of Customization

Quality of Features

Vendor Support

Business Value Created

Breadth of Features

Usability and Intuitiveness

Availability and Quality of Training

Ease of Implementation

Ease of Data Integration

Product Strategy and Rate of Improvement

Ease of IT Administration