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Best Machine Learning Software - Page 4

Shalaka Joshi
SJ
Researched and written by Shalaka Joshi

Machine learning software leverages algorithms to automate complex decision-making and generate predictions, eliminating the need for manual rule configuration. Machine learning solutions improve the speed and accuracy of desired outputs by constantly refining them as the application digests more training data. Machine learning software improves processes and introduces efficiency in multiple industries, ranging from financial services to agriculture. Common applications include process automation, customer service, security risk identification, and contextual collaboration.

Notably, end users of machine learning-powered applications do not interact with the algorithm directly. Instead, machine learning powers the backend of the artificial intelligence (AI) that users interact with. Machine learning platforms function differently from machine learning operationalization (MLOps) platforms by focusing on model development and training rather than deployment monitoring and lifecycle management.

To qualify for inclusion in the Machine Learning category, a product must:

Offer an algorithm that learns and adapts based on data
Consume data inputs from a variety of data pools
Ingest data from structured, unstructured, or streaming sources, including local files, cloud storage, databases, or APIs
Be the source of intelligent learning capabilities for applications
Provide an output that solves a specific issue based on the learned data
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Featured Machine Learning Software At A Glance

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Alteryx
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Highest Performer:
Easiest to Use:
Top Trending:
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Easiest to Use:
Top Trending:

G2 takes pride in showing unbiased reviews on user satisfaction in our ratings and reports. We do not allow paid placements in any of our ratings, rankings, or reports. Learn about our scoring methodologies.

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312 Listings in Machine Learning Available
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Conjecture is a framework for building machine learning models in Hadoop using the Scalding DSL that enable the development of statistical models as viable components in a wide range of product settin

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 64% Small-Business
    • 18% Enterprise
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Conjecture features and usability ratings that predict user satisfaction
    6.7
    Has the product been a good partner in doing business?
    Average: 8.7
    8.1
    Ease of Use
    Average: 8.5
    8.8
    Quality of Support
    Average: 8.4
    8.3
    Ease of Admin
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    2018
    HQ Location
    Perth, Australia
    LinkedIn® Page
    www.linkedin.com
Product Description
How are these determined?Information
This description is provided by the seller.

Conjecture is a framework for building machine learning models in Hadoop using the Scalding DSL that enable the development of statistical models as viable components in a wide range of product settin

Users
No information available
Industries
No information available
Market Segment
  • 64% Small-Business
  • 18% Enterprise
Conjecture features and usability ratings that predict user satisfaction
6.7
Has the product been a good partner in doing business?
Average: 8.7
8.1
Ease of Use
Average: 8.5
8.8
Quality of Support
Average: 8.4
8.3
Ease of Admin
Average: 8.5
Seller Details
Year Founded
2018
HQ Location
Perth, Australia
LinkedIn® Page
www.linkedin.com
(13)4.4 out of 5
11th Easiest To Use in Machine Learning software
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    XGBoost is an optimized distributed gradient boosting library that is efficient, flexible and portable, it implements machine learning algorithms under the Gradient Boosting framework and provides a p

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 46% Small-Business
    • 31% Enterprise
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • XGBoost features and usability ratings that predict user satisfaction
    8.3
    Has the product been a good partner in doing business?
    Average: 8.7
    8.9
    Ease of Use
    Average: 8.5
    7.6
    Quality of Support
    Average: 8.4
    8.3
    Ease of Admin
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    XGBoost
    Year Founded
    2008
    HQ Location
    San Francisco, US
    Twitter
    @github
    2,604,424 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    1 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

XGBoost is an optimized distributed gradient boosting library that is efficient, flexible and portable, it implements machine learning algorithms under the Gradient Boosting framework and provides a p

Users
No information available
Industries
No information available
Market Segment
  • 46% Small-Business
  • 31% Enterprise
XGBoost features and usability ratings that predict user satisfaction
8.3
Has the product been a good partner in doing business?
Average: 8.7
8.9
Ease of Use
Average: 8.5
7.6
Quality of Support
Average: 8.4
8.3
Ease of Admin
Average: 8.5
Seller Details
Seller
XGBoost
Year Founded
2008
HQ Location
San Francisco, US
Twitter
@github
2,604,424 Twitter followers
LinkedIn® Page
www.linkedin.com
1 employees on LinkedIn®

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  • Overview
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  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Apache PredictionIO is an open source Machine Learning Server built on top of a state-of-the-art open source stack for developers and data scientists to create predictive engines for any machine learn

    Users
    No information available
    Industries
    • Computer Software
    Market Segment
    • 39% Small-Business
    • 33% Mid-Market
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Apache PredictionIO features and usability ratings that predict user satisfaction
    10.0
    Has the product been a good partner in doing business?
    Average: 8.7
    8.8
    Ease of Use
    Average: 8.5
    8.4
    Quality of Support
    Average: 8.4
    10.0
    Ease of Admin
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    1999
    HQ Location
    Wakefield, MA
    Twitter
    @TheASF
    65,768 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    2,345 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Apache PredictionIO is an open source Machine Learning Server built on top of a state-of-the-art open source stack for developers and data scientists to create predictive engines for any machine learn

Users
No information available
Industries
  • Computer Software
Market Segment
  • 39% Small-Business
  • 33% Mid-Market
Apache PredictionIO features and usability ratings that predict user satisfaction
10.0
Has the product been a good partner in doing business?
Average: 8.7
8.8
Ease of Use
Average: 8.5
8.4
Quality of Support
Average: 8.4
10.0
Ease of Admin
Average: 8.5
Seller Details
Year Founded
1999
HQ Location
Wakefield, MA
Twitter
@TheASF
65,768 Twitter followers
LinkedIn® Page
www.linkedin.com
2,345 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Milk is a machine learning toolkit in Python that focuses on supervised classification with several classifiers available: SVMs (based on libsvm), k-NN, random forests, decision trees. It also perform

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 50% Mid-Market
    • 42% Small-Business
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • MILK features and usability ratings that predict user satisfaction
    7.8
    Has the product been a good partner in doing business?
    Average: 8.7
    7.3
    Ease of Use
    Average: 8.5
    7.0
    Quality of Support
    Average: 8.4
    7.8
    Ease of Admin
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    MILK
    Year Founded
    2008
    HQ Location
    New York, NY
    Twitter
    @github
    2,604,424 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    5,749 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Milk is a machine learning toolkit in Python that focuses on supervised classification with several classifiers available: SVMs (based on libsvm), k-NN, random forests, decision trees. It also perform

Users
No information available
Industries
No information available
Market Segment
  • 50% Mid-Market
  • 42% Small-Business
MILK features and usability ratings that predict user satisfaction
7.8
Has the product been a good partner in doing business?
Average: 8.7
7.3
Ease of Use
Average: 8.5
7.0
Quality of Support
Average: 8.4
7.8
Ease of Admin
Average: 8.5
Seller Details
Seller
MILK
Year Founded
2008
HQ Location
New York, NY
Twitter
@github
2,604,424 Twitter followers
LinkedIn® Page
www.linkedin.com
5,749 employees on LinkedIn®
(22)4.5 out of 5
View top Consulting Services for PyTorch
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Choose Your Path: Install PyTorch Locally or Launch Instantly on Supported Cloud Platforms

    Users
    No information available
    Industries
    • Computer Software
    Market Segment
    • 41% Mid-Market
    • 41% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • PyTorch Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    7
    Machine Learning
    5
    Documentation
    4
    Model Variety
    4
    Quality
    3
    Cons
    Difficult Learning
    3
    Poor Documentation
    2
    Compatibility Issues
    1
    Complexity
    1
    Difficult Navigation
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • PyTorch features and usability ratings that predict user satisfaction
    8.3
    Has the product been a good partner in doing business?
    Average: 8.7
    8.6
    Ease of Use
    Average: 8.5
    7.9
    Quality of Support
    Average: 8.4
    8.3
    Ease of Admin
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Jetware
    Year Founded
    2017
    HQ Location
    Roma, IT
    Twitter
    @jetware_io
    25 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    1 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Choose Your Path: Install PyTorch Locally or Launch Instantly on Supported Cloud Platforms

Users
No information available
Industries
  • Computer Software
Market Segment
  • 41% Mid-Market
  • 41% Small-Business
PyTorch Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
7
Machine Learning
5
Documentation
4
Model Variety
4
Quality
3
Cons
Difficult Learning
3
Poor Documentation
2
Compatibility Issues
1
Complexity
1
Difficult Navigation
1
PyTorch features and usability ratings that predict user satisfaction
8.3
Has the product been a good partner in doing business?
Average: 8.7
8.6
Ease of Use
Average: 8.5
7.9
Quality of Support
Average: 8.4
8.3
Ease of Admin
Average: 8.5
Seller Details
Seller
Jetware
Year Founded
2017
HQ Location
Roma, IT
Twitter
@jetware_io
25 Twitter followers
LinkedIn® Page
www.linkedin.com
1 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    DecisionTree.jl is a Julia classifier with the implimentation of the ID3 algorithm with post pruning (pessimistic pruning), parallelized bagging (random forests), adaptive boosting (decision stumps),

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 36% Mid-Market
    • 36% Small-Business
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • DecisionTree.jl features and usability ratings that predict user satisfaction
    8.3
    Has the product been a good partner in doing business?
    Average: 8.7
    7.4
    Ease of Use
    Average: 8.5
    6.9
    Quality of Support
    Average: 8.4
    6.7
    Ease of Admin
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    HQ Location
    N/A
    LinkedIn® Page
    www.linkedin.com
    1 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

DecisionTree.jl is a Julia classifier with the implimentation of the ID3 algorithm with post pruning (pessimistic pruning), parallelized bagging (random forests), adaptive boosting (decision stumps),

Users
No information available
Industries
No information available
Market Segment
  • 36% Mid-Market
  • 36% Small-Business
DecisionTree.jl features and usability ratings that predict user satisfaction
8.3
Has the product been a good partner in doing business?
Average: 8.7
7.4
Ease of Use
Average: 8.5
6.9
Quality of Support
Average: 8.4
6.7
Ease of Admin
Average: 8.5
Seller Details
HQ Location
N/A
LinkedIn® Page
www.linkedin.com
1 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Apache Mahout is a software that build an environment for quickly creating scalable performant machine learning applications, it provides three major features: A simple and extensible programming envi

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 46% Mid-Market
    • 31% Enterprise
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Mahout features and usability ratings that predict user satisfaction
    8.6
    Has the product been a good partner in doing business?
    Average: 8.7
    7.1
    Ease of Use
    Average: 8.5
    8.8
    Quality of Support
    Average: 8.4
    7.6
    Ease of Admin
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Year Founded
    1999
    HQ Location
    Wakefield, MA
    Twitter
    @TheASF
    65,768 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    2,345 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Apache Mahout is a software that build an environment for quickly creating scalable performant machine learning applications, it provides three major features: A simple and extensible programming envi

Users
No information available
Industries
No information available
Market Segment
  • 46% Mid-Market
  • 31% Enterprise
Mahout features and usability ratings that predict user satisfaction
8.6
Has the product been a good partner in doing business?
Average: 8.7
7.1
Ease of Use
Average: 8.5
8.8
Quality of Support
Average: 8.4
7.6
Ease of Admin
Average: 8.5
Seller Details
Year Founded
1999
HQ Location
Wakefield, MA
Twitter
@TheASF
65,768 Twitter followers
LinkedIn® Page
www.linkedin.com
2,345 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Recommender is a tool that analyzes the the feedback of some users (implicit and explicit) and their preferences for some items to learns patterns and predicts the most suitable products for a particu

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 45% Mid-Market
    • 27% Enterprise
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Recommender features and usability ratings that predict user satisfaction
    7.8
    Has the product been a good partner in doing business?
    Average: 8.7
    9.6
    Ease of Use
    Average: 8.5
    8.8
    Quality of Support
    Average: 8.4
    8.3
    Ease of Admin
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Google
    Year Founded
    1998
    HQ Location
    Mountain View, CA
    Twitter
    @google
    31,716,915 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    325,307 employees on LinkedIn®
    Ownership
    NASDAQ:GOOG
Product Description
How are these determined?Information
This description is provided by the seller.

Recommender is a tool that analyzes the the feedback of some users (implicit and explicit) and their preferences for some items to learns patterns and predicts the most suitable products for a particu

Users
No information available
Industries
No information available
Market Segment
  • 45% Mid-Market
  • 27% Enterprise
Recommender features and usability ratings that predict user satisfaction
7.8
Has the product been a good partner in doing business?
Average: 8.7
9.6
Ease of Use
Average: 8.5
8.8
Quality of Support
Average: 8.4
8.3
Ease of Admin
Average: 8.5
Seller Details
Seller
Google
Year Founded
1998
HQ Location
Mountain View, CA
Twitter
@google
31,716,915 Twitter followers
LinkedIn® Page
www.linkedin.com
325,307 employees on LinkedIn®
Ownership
NASDAQ:GOOG
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Pattern Recognition and Machine Learning is a Matlab implementation of the algorithms.

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 45% Small-Business
    • 27% Mid-Market
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Patern Recognition and Machine Learning Toolbox features and usability ratings that predict user satisfaction
    8.3
    Has the product been a good partner in doing business?
    Average: 8.7
    7.6
    Ease of Use
    Average: 8.5
    7.6
    Quality of Support
    Average: 8.4
    8.9
    Ease of Admin
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    HQ Location
    N/A
    Twitter
    @michigangraham
    117 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    1 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Pattern Recognition and Machine Learning is a Matlab implementation of the algorithms.

Users
No information available
Industries
No information available
Market Segment
  • 45% Small-Business
  • 27% Mid-Market
Patern Recognition and Machine Learning Toolbox features and usability ratings that predict user satisfaction
8.3
Has the product been a good partner in doing business?
Average: 8.7
7.6
Ease of Use
Average: 8.5
7.6
Quality of Support
Average: 8.4
8.9
Ease of Admin
Average: 8.5
Seller Details
HQ Location
N/A
Twitter
@michigangraham
117 Twitter followers
LinkedIn® Page
www.linkedin.com
1 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Vowpal Wabbit is a machine learning system that pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learnin

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 46% Mid-Market
    • 31% Enterprise
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Vowpal Wabbit features and usability ratings that predict user satisfaction
    0.0
    No information available
    8.8
    Ease of Use
    Average: 8.5
    8.0
    Quality of Support
    Average: 8.4
    6.7
    Ease of Admin
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    HQ Location
    N/A
    LinkedIn® Page
    www.linkedin.com
    1 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Vowpal Wabbit is a machine learning system that pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learnin

Users
No information available
Industries
No information available
Market Segment
  • 46% Mid-Market
  • 31% Enterprise
Vowpal Wabbit features and usability ratings that predict user satisfaction
0.0
No information available
8.8
Ease of Use
Average: 8.5
8.0
Quality of Support
Average: 8.4
6.7
Ease of Admin
Average: 8.5
Seller Details
HQ Location
N/A
LinkedIn® Page
www.linkedin.com
1 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Ganitha is an open-source library (derived from the Sanskrit word for mathematics, or science of computation) is a Scalding library with a focus on machine-learning and statistical analysis.

    Users
    No information available
    Industries
    • Marketing and Advertising
    Market Segment
    • 73% Mid-Market
    • 27% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Ganitha Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Big Data
    4
    Ease of Use
    4
    Model Variety
    4
    Integrations
    3
    Flexibility
    2
    Cons
    Poor Documentation
    3
    Difficult Learning
    2
    Learning Curve
    1
    Limited Customization
    1
    Limited Features
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Ganitha features and usability ratings that predict user satisfaction
    0.0
    No information available
    6.7
    Ease of Use
    Average: 8.5
    6.5
    Quality of Support
    Average: 8.4
    0.0
    No information available
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Tresata
    Year Founded
    2011
    HQ Location
    Charlotte, NC
    LinkedIn® Page
    www.linkedin.com
    23 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Ganitha is an open-source library (derived from the Sanskrit word for mathematics, or science of computation) is a Scalding library with a focus on machine-learning and statistical analysis.

Users
No information available
Industries
  • Marketing and Advertising
Market Segment
  • 73% Mid-Market
  • 27% Small-Business
Ganitha Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Big Data
4
Ease of Use
4
Model Variety
4
Integrations
3
Flexibility
2
Cons
Poor Documentation
3
Difficult Learning
2
Learning Curve
1
Limited Customization
1
Limited Features
1
Ganitha features and usability ratings that predict user satisfaction
0.0
No information available
6.7
Ease of Use
Average: 8.5
6.5
Quality of Support
Average: 8.4
0.0
No information available
Seller Details
Seller
Tresata
Year Founded
2011
HQ Location
Charlotte, NC
LinkedIn® Page
www.linkedin.com
23 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Vivas.AI is a one-stop marketplace to access a wide range of AI models for various use cases across industries. Vivas.AI shifts the balance of power from ML engineers toward application engineers. A

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 50% Mid-Market
    • 50% Small-Business
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Vivas.AI features and usability ratings that predict user satisfaction
    8.3
    Has the product been a good partner in doing business?
    Average: 8.7
    8.8
    Ease of Use
    Average: 8.5
    8.3
    Quality of Support
    Average: 8.4
    9.2
    Ease of Admin
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    Vivas.AI
    Year Founded
    2022
    HQ Location
    Chennai, IN
    Twitter
    @vivas_ai
    5 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    2 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Vivas.AI is a one-stop marketplace to access a wide range of AI models for various use cases across industries. Vivas.AI shifts the balance of power from ML engineers toward application engineers. A

Users
No information available
Industries
No information available
Market Segment
  • 50% Mid-Market
  • 50% Small-Business
Vivas.AI features and usability ratings that predict user satisfaction
8.3
Has the product been a good partner in doing business?
Average: 8.7
8.8
Ease of Use
Average: 8.5
8.3
Quality of Support
Average: 8.4
9.2
Ease of Admin
Average: 8.5
Seller Details
Seller
Vivas.AI
Year Founded
2022
HQ Location
Chennai, IN
Twitter
@vivas_ai
5 Twitter followers
LinkedIn® Page
www.linkedin.com
2 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Breeze is a numerical processing library for Scala.

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 67% Mid-Market
    • 33% Small-Business
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Beeze features and usability ratings that predict user satisfaction
    6.7
    Has the product been a good partner in doing business?
    Average: 8.7
    7.3
    Ease of Use
    Average: 8.5
    7.1
    Quality of Support
    Average: 8.4
    7.9
    Ease of Admin
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    ScalaNLP
    HQ Location
    N/A
    Twitter
    @ScalaNLP
    194 Twitter followers
    LinkedIn® Page
    www.linkedin.com
    1 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

Breeze is a numerical processing library for Scala.

Users
No information available
Industries
No information available
Market Segment
  • 67% Mid-Market
  • 33% Small-Business
Beeze features and usability ratings that predict user satisfaction
6.7
Has the product been a good partner in doing business?
Average: 8.7
7.3
Ease of Use
Average: 8.5
7.1
Quality of Support
Average: 8.4
7.9
Ease of Admin
Average: 8.5
Seller Details
Seller
ScalaNLP
HQ Location
N/A
Twitter
@ScalaNLP
194 Twitter followers
LinkedIn® Page
www.linkedin.com
1 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    DagsHub is a platform that allows you to easily create high-quality datasets for better model performance A single AI platform to curate vision, audio, and document data - automate labeling workflo

    Users
    No information available
    Industries
    • Computer Software
    Market Segment
    • 50% Small-Business
    • 43% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • DagsHub Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Data Management
    12
    Model Management
    12
    Collaboration
    11
    Features
    10
    Integrated Platform
    10
    Cons
    Limited Functionality
    2
    Error Handling
    1
    Expensive
    1
    Limited Customization
    1
    Limited Free Access
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • DagsHub features and usability ratings that predict user satisfaction
    9.4
    Has the product been a good partner in doing business?
    Average: 8.7
    9.2
    Ease of Use
    Average: 8.5
    9.3
    Quality of Support
    Average: 8.4
    9.2
    Ease of Admin
    Average: 8.5
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    DagsHub
    HQ Location
    San Francisco, US
    LinkedIn® Page
    www.linkedin.com
    14 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

DagsHub is a platform that allows you to easily create high-quality datasets for better model performance A single AI platform to curate vision, audio, and document data - automate labeling workflo

Users
No information available
Industries
  • Computer Software
Market Segment
  • 50% Small-Business
  • 43% Mid-Market
DagsHub Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Data Management
12
Model Management
12
Collaboration
11
Features
10
Integrated Platform
10
Cons
Limited Functionality
2
Error Handling
1
Expensive
1
Limited Customization
1
Limited Free Access
1
DagsHub features and usability ratings that predict user satisfaction
9.4
Has the product been a good partner in doing business?
Average: 8.7
9.2
Ease of Use
Average: 8.5
9.3
Quality of Support
Average: 8.4
9.2
Ease of Admin
Average: 8.5
Seller Details
Seller
DagsHub
HQ Location
San Francisco, US
LinkedIn® Page
www.linkedin.com
14 employees on LinkedIn®
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    MLKit is a machine learning framework written in Swift that features machine learning algorithms that deal with the topic of regression to provide developers with a toolkit to create products that can

    Users
    No information available
    Industries
    No information available
    Market Segment
    • 46% Small-Business
    • 31% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • MLKit Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Integrations
    1
    Model Variety
    1
    Usage Frequency
    1
    Cons
    This product has not yet received any negative sentiments.
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • MLKit features and usability ratings that predict user satisfaction
    0.0
    No information available
    9.3
    Ease of Use
    Average: 8.5
    9.2
    Quality of Support
    Average: 8.4
    0.0
    No information available
  • Seller Details
    Expand/Collapse Seller Details
  • Seller Details
    Seller
    MLKit
    HQ Location
    N/A
    LinkedIn® Page
    www.linkedin.com
    1 employees on LinkedIn®
Product Description
How are these determined?Information
This description is provided by the seller.

MLKit is a machine learning framework written in Swift that features machine learning algorithms that deal with the topic of regression to provide developers with a toolkit to create products that can

Users
No information available
Industries
No information available
Market Segment
  • 46% Small-Business
  • 31% Mid-Market
MLKit Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Integrations
1
Model Variety
1
Usage Frequency
1
Cons
This product has not yet received any negative sentiments.
MLKit features and usability ratings that predict user satisfaction
0.0
No information available
9.3
Ease of Use
Average: 8.5
9.2
Quality of Support
Average: 8.4
0.0
No information available
Seller Details
Seller
MLKit
HQ Location
N/A
LinkedIn® Page
www.linkedin.com
1 employees on LinkedIn®

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