Machine Learning Platforms (ML) Platform

Machine Learning Platforms

What is Machine Learning Platforms Platform?

A comprehensive collection of tools, libraries and resources that allows data scientists and machine learning engineers to build and deploy Machine Learning (ML) powered business applications. ML tools automate the delivery life-cycle of predictive applications capable of processing big data using machine learning algorithms.

Common Features

  • Data Ingestion
  • Data Pre-Processing
  • Feature Engineering
  • Algorithm Diversity
  • Model Training
  • Model Tuning
  • Model Monitoring and Management
  • Performance and Scalability
  • Ensembling
  • Openness and Flexibility
  • Explainability
  • Data Exploration and Visualization
  • Pre-Packaged AI/ML Services
  • Data Labeling
  • Algorithm Recommendation

Top Machine Learning Platforms (ML) Platform

2024 Data Quadrant Awards

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At SoftwareReviews, we take pride in recognizing excellence. Each year, we present the Data Quadrant Awards to top-performing software products based solely on authentic user reviews, without any paid placements or analyst opinions. These awards highlight software products that excel in terms of features, vendor capabilities, and customer relationships, earning them the highest overall rankings.

At SoftwareReviews, we take pride in recognizing excellence. Each year, we present the Emotional Footprint Awards to top-performing software products based solely on authentic user reviews, without any paid placements or analyst opinions. These awards shine a spotlight on software vendors who excel in crafting and nurturing strong customer relationships.

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Products: 12
Next Award: Jun 2025

Top Machine Learning Platforms Platform 2024

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Composite Score
8.8 /10
CX Score
9.0 /10

MATLAB is a high-level language and interactive environment for numerical computation, visualization, and programming. It is a programming and numeric computing platform used by millions of engineers and scientists to analyze data, develop algorithms, and create models.

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Pros

  • Reliable
  • Unique Features
  • Respectful
  • Client Friendly Policies
Badge Winner
Badge Winner
Composite Score
8.7 /10
CX Score
8.9 /10

Machine Learning Studio is a powerfully simple browser-based, visual drag-and-drop authoring environment where no coding is necessary. Go from idea to deployment in a matter of clicks. Microsoft Azure Machine Learning Studio is a collaborative, drag-and-drop tool you can use to build, test, and deploy predictive analytics solutions on your data. Machine Learning Studio publishes models as web services that can easily be consumed by custom apps or BI tools such as Excel.

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Pros

  • Performance Enhancing
  • Respectful
  • Includes Product Enhancements
  • Reliable
Badge Winner
Badge Winner
Composite Score
8.7 /10
CX Score
8.9 /10

Cloud Machine Learning Engine is a managed service that lets developers and data scientists build and run superior machine learning models in production. Cloud ML Engine offers training and prediction services, which can be used together or individually. It has been used by enterprises to solve problems ranging from identifying clouds in satellite images, ensuring food safety, and responding four times faster to customer emails. The training and prediction services within ML Engine are now referred to as AI Platform Training and AI Platform Prediction.

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Pros

  • Inspires Innovation
  • Performance Enhancing
  • Effective Service
  • Respectful
Badge Winner
Badge Winner
Composite Score
8.4 /10
CX Score
8.7 /10

Amazon Machine Learning is an Amazon Web Services product that allows a developer to discover patterns in end-user data through algorithms, construct mathematical models based on these patterns and then create and implement predictive applications.

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Pros

  • Reliable
  • Security Protects
  • Respectful
  • Continually Improving Product
Composite Score
8.2 /10
CX Score
8.5 /10

TFX is an end-to-end platform for deploying production ML pipelines. A TFX pipeline is a sequence of components that implement an ML pipeline which is specifically designed for scalable, high-performance machine learning tasks. Components are built using TFX libraries which can also be used individually. When you're ready to move your models from research to production, TFX can be used to create and manage a production pipeline.

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Pros

  • Helps Innovate
  • Continually Improving Product
  • Reliable
  • Enables Productivity
Badge Winner
Composite Score
8.1 /10
CX Score
8.4 /10

The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals.

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Pros

  • Continually Improving Product
  • Effective Service
  • Fair
  • Client's Interest First
Badge Winner
Badge Winner
Microsoft Corporation

Microsoft Fabric

Composite Score
8.0 /10
CX Score
8.5 /10

Microsoft Fabric is a platform that allows users to get, create, share, and visualize data using an array of tools. Give your data teams all the tools they need in a unified experience that helps reduce the cost and effort of data integration, governance, and security.

Pros

  • Helps Innovate
  • Continually Improving Product
  • Reliable
  • Performance Enhancing
Dataiku

Dataiku

Composite Score
8.0 /10
CX Score
8.2 /10

Dataiku is the platform democratizing access to data and enabling enterprises to build their own path to AI in a human-centric way. With Dataiku, everyone can get involved in data and AI projects on a single platform for design and production that delivers use cases in days, not months. No matter where they sit, they work in a safe and governed way that helps manage risk and create trust to drive high-quality outputs and value for your business.

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Pros

  • Helps Innovate
  • Continually Improving Product
  • Reliable
  • Performance Enhancing
Badge Winner
Badge Winner
Eclipse Foundation Inc

Eclipse Deeplearning4j

Composite Score
7.9 /10
CX Score
8.1 /10

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.

Pros

  • Helps Innovate
  • Continually Improving Product
  • Reliable
  • Performance Enhancing
Composite Score
7.7 /10
CX Score
7.9 /10

KNIME offers a complete platform for end-to-end data science, from creating analytical models, to deploying them and sharing insights within the organization, through to data apps and services. The free and open source KNIME Analytics Platform allows users to easily build analyses with an intuitive, low-code/no-code interface. KNIME Business Hub enables users across different disciplines to collaborate and productionize analytical solutions created using KNIME Analytics Platform.

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Pros

  • Inspires Innovation
  • Efficient Service
  • Helps Innovate
  • Acts with Integrity