10 Best Machine Learning Platforms in 2024

Have you ever wondered why you keep getting suggestions to watch videos from Netflix’s recommendations based on what you have watched earlier?

Is this magic? Machine learning is no less than magic. It gives you recommendations based on your saved data to create a user-friendly experience.

So, being an entrepreneur, if you have decided to develop machine learning-based apps, then you must know the ins and outs of machine learning platforms. This comprehensive guide will help you to find the best platform for machine learning.

What is Machine Learning?

Machine learning is a subset of artificial intelligence that allows computers to learn and improve without being explicitly programmed. It involves developing models and algorithms capable of analyzing data, identifying patterns, and making decisions based on that data.

In simple language, it is a state-of-the-art application of artificial intelligence that gives the ability to the system to learn and improve automatically through experiences.

ML is definitely evolving over these years to give a whole new experience to the users based on their interests. Many businesses, like Tinder, and Snapchat, have taken the benefit of ML through mobile app solutions to improve customer experience, gain customer loyalty, increase brand awareness, and target audience filtration.

Build a machine learning powered app like Netflix with us.

We have experience developing machine learning-based apps for various use cases.

Cta Image

Introduction to Machine Learning Platforms

A machine learning platform is used for automating and quicken the delivery lifecycle of predictive applications which have capabilities to process big data.

A good ML platform allows a data scientist to build blocks to find the solutions for any data science problem. Moreover, the data scientists get complete freedom with an environment where they can easily incorporate the solutions into products. Moving ahead, let’s check out the top AI ML platforms for machine learning 2024.

Best Machine Learning Platforms

Face recognition, training and tuning are some of the essential machine learning capabilities. We have listed down the best machine learning software below.

  1. KNIME Analytics Platform

    KNIME Analytics Platform is a well-known online machine learning platform, which is a free open-source platform that provides end-to-end data analysis, integration, and reporting. With the KNIME Analytics Platform, data scientists can easily enable the creation of visual workflows via a drag-and-drop-style graphical interface. It will not require knowledge of coding.

    To build workflows, a user gets to choose from more than 2000 nodes. KNIME Analytics allows developers to perform various actions; from basic I/O to data manipulations, transformations, and data mining. The best part of KNIME Analytics is that it consolidates the entire function process into a single workflow.

    Top Features:

    • Parallel execution on multi-core systems
    • Offers scalability through sophisticated data handling
    • Simple extensibility via a well-defined API for plugin extensions

    Want to download and try KNIME Analytics Platform?

  2. TIBCO Software

    TIBCO is a data science platform that supports the entire analytics lifecycle with capabilities to include cloud-based analytics that integrates with many open source libraries.

    TIBCO data science allows the user to prepare data and do the model building, deployment, and monitoring. It is widely known for use cases, such as product refinement and business exploration.

    Top Features:

    • Automatically detects the locations and visualizes those data as an interactive map
    • Can analyze data in many visualization types, such as tables and charts
    • Can access real-time streaming and spot issues

    Want to download and try TIBCO Software?

  3. Amazon SageMaker

    Amazon SageMaker is a cloud machine-learning platform that allows developers to create, train, and deploy machine learning models. Data scientists or developers can easily deploy machine learning models on embedded systems and edge devices.

    It is developed by Amazon Web Services (AWS) that offers the broadest machine and deepest set of learning services and supporting cloud infrastructure.

    Top Features:

    • Build highly accurate training datasets
    • Provides a visual interface to analyze the debug data for the easy inspection process
    • No need to break down the data set into multiple chunks

    Want to try and download Amazon SageMaker?

  4. Alteryx Analytics

    Alteryx is the best data science platform that accelerates digital transformation. It offers data accessibility and data science processes.

    Alteryx provides data scientists with a platform that helps them build models in a workflow.

    Their vision is to make it easy to use for companies to cultivate a data analytics culture without the requirement of data scientists. In self-service data analytics, Alteryx always leads.

    Top Features:

    • Automate manual data tasks into repeatable analytics workflows
    • Freedom to deploy and manage analytic models
    • Support almost every data source and visualization tool

    Want to try and download Alteryx Analytics?

  5. SAS

    SAS is a data science and analytics software vendor that offers a robust suite of advanced analytics and data science products. The best part of considering the SAS platform is that you can easily access data in any format and from any source.

    It automatically generates a pipeline that dynamically adjusts to the data. It also includes natural language generation for project management. SAS Model Management allows users to register SAS and open-source models within projects or as standalone models.

    Top Features:

    • Allows to explore data from within Model Studio and launch directly into SAS Visual Analytics
    • Visual interface for the entire analytical lifecycle process
    • View training data within each node in Model Studio

    Want to try and download SAS?

  6. H2O.ai

    H2O.ai offers a wide range of AI platforms and data science platforms to expert data scientists. It is a fully open-source platform, which is a distributed in-memory ML platform with linear scalability.

    H2O supports statistical and machine learning algorithms for those who are looking for deep learning platforms because deep learning is one of the significant advantages of it.

    It offers Deep Water for deep learning, where H2O continues to lead in data science and machine learning unified platforms.

    Top Features:

    • Process large text blocks and build models with Natural Language Processing
    • Has image processing capabilities using over 30 pre-trained image transformers and models
    • Automatically generates visualizations and creates data plots

    Want to try and download H2O.ai?

  7. Databricks Unified Analytics Platform

    It offers a cloud and Apache Spark-based unified analytics platform, which is a combination of data engineering and data science functionality.

    The one who is working on the Databricks Unified Analytics platform gets exclusive features for real-time enablement on AWS, high performance, and best operation results.

    One can simply access the preconfigured ML environments with a single-click feature for Augmented Machine Learning with popular frameworks.

    Top Features:

    • Highly reliable and performant data pipelines
    • Productive data science at scale
    • End-to-end data security and compliance

    Want to try and download Databricks Unified?

  8. Microsoft Azure Machine Learning Studio

    Microsoft offers its services in the data science and machine-learning markets through its Azure software products.

    The cloud-based Azure Machine Learning Studio is perfectly designed for those who want to build, test, and execute predictive analytics, and machine learning solutions on their data. Azure is one of the most liked platforms in the data science and machine learning markets.

    Apart from this, Microsoft Azure allows customers to easily build, deploy, and share advanced analytics solutions in the cloud.

    Top Features:

    • Integrates with existing DevOps processes and helps to manage the complete ML lifecycle
    • Understand models with interpretability and protect data
    • Provides the best support for open-source frameworks and languages

    Want to try and download Microsoft Azure?

  9. DataRobot

    DataRobot offers an enterprise AI machine learning platform that makes it fast and easy to maintain, build, and deploy AI.

    It includes Automated Machine Learning, Automated Time Series, and MLOps which are independent and fully integrated tools.

    All can be easily deployed in various ways according to the business requirements. It helps you to solve business problems by finding the best predictive model for your data.

    Top Features:

    • Allows to build innovative new deep learning models from incredibly diverse types of data
    • Monitor models via a centralized dashboard to see usage in real-time
    • Provides fully explainable AI through human-friendly visual insights

    Want to try and download DataRobot?

  10. RapidMiner

    RapidMiner offers a data science platform to help people for building and operating AI solutions. It covers the entire lifecycle of the AI production process; from data exploration and data preparation to model building, ML models deployment, and model operations.

    It comes with the depth that is essential for a data scientist to simplify AI via a visual user interface that can easily streamline the process of building and understanding complex models.

    Top Features:

    • The powerful visual programming environment
    • Access, load, and analyze any type of data
    • Efficiently build and deliver better models faster

    Want to try and download RapidMiner?

    So, we have gone through the best platforms for machine learning along with their features and download option. In case, if you are finding it quite difficult to choose one, no problem. We have compared these platforms in the next section. Let’s have a look at the comparison.

Want to Hire ML Developers?

Want to validate your app idea? Get a free machine learning consulting for your project.

Machine Learning Platforms Comparison

With the help of Gartner, we have made a comparison table for ML platforms based on the reviews of clients and customers.

Many clients and customers rely on Gartner to look up for business suggestions because Gartner is a leading and advisory company. Please feel free to check machine learning platform comparison below.

LogoPlatformOverall RatingWould Recommend
Alteryx4.7 94% Yes percentage
AWS4.7 83% Yes percentage
Databricks4.5 91% Yes percentage
DataRobot4.8 94% Yes percentage
H2O.ai4.8 96% Yes percentage
KNIME4.8 100% Yes percentage
Microsoft4.5 85% Yes percentage
RapidMiner4.7 92% Yes percentage
SAS4.6 86% Yes percentage
TIBCO4.6 85% Yes percentage

To make it easy for you, we have compared all the platforms based on their ‘Overall Ratings’ and ‘Would Recommend’ percentages. You can check all the platforms with their received ratings & recommendation percentage and decide which platform is the best for your project.

Comparing all the platforms based on the recommendation percentage, KNIME has got 100%, which is the highest with 34 customer reviews. In fact, this platform is adopted by millions of customers.

Do You Have a Project in Mind?

Get a free consultation from a web expert to discuss your requirements and take your project to the next level.

Introduction to Machine Learning Tools

Before you know the various tools for machine learning, you must know their importance because mastering ML will allow you to perform many tasks.

Machine learning comes with an extensive collection of ML tools, platforms, and software products that let you train your models, discover new methods, and create your own algorithms. Machine learning Here’s the list of machine learning tools:

Best Machine Learning Tools

Here, we have listed the best machine learning tools and compared them based on their platforms, language, features, benefits, and cost.

ToolSupported PlatformLanguageAlgorithms/ FeaturesBenefitsTool Cost
Scikit-learnLinux, Mac OS, WindowsPython, Cython, C, C++
  • Classification
  • Regression
  • Clustering
  • Preprocessing
  • Model Selection
  • Dimensionality reduction
  • Understandable documentation is provided
  • Parameters for any specific algorithm can be changed while calling objects.
PyTorchLinux, Mac OS, WindowsPython, C++, CUDA
  • Autograd Module
  • Optim Module
  • nn Module
  • Helps in creating computational graphs
  • Ease of use because of the hybrid front-end
TensorFlowLinux, Mac OS, WindowsPython, C++, CUDAProvides a library for dataflow programming
  • Used in 2 ways – by script tags or by installing through NPM
  • Help for human pose estimation
WekaLinux, Mac OS, WindowsJava
  • Data preparation
  • Classification
  • Regression
  • Clustering
  • Visualization
  • Association rules mining
  • Provides online courses for training
  • Easy to understand algorithms
  • Good for students as well
KNIMELinux, Mac OS, WindowsJava
  • Can work with large data volume
  • Supports text mining & image mining through plugins
  • Can work as a SAS alternative
  • Easy to deploy and install
  • Easy to learn
ColabCloud ServiceSupports libraries of PyTorch, Keras, TensorFlow, and OpenCV
  • Can use it from your google drive
Mahout – ApacheCross-platformJava Scala
  • Preprocessors
  • Regression
  • Clustering
  • Recommenders
  • Distributed Linear Algebra
  • Works for large data sets
  • Simple
  • Extensible
  • Classification
  • Regression
  • Distribution
  • Clustering
  • Hypothesis Tests & Kernel Methods
  • Image, Audio & Signal. & Vision
  • Libraries are made available from the source code and also through executable installer & NuGet package manager
ShogunWindows Linux UNIX Mac OSC++
  • Regression
  • Classification
  • Clustering
  • Support vector machines
  • Dimensionality reduction Online learning
  • Can process large data-sets
  • Easy to use
  • Provides good customer support
  • Offers good features and functionalities
Keras.ioCross-platformPythonAPI for neural networks
  • User-friendly
  • Modular
  • Extensible
  • Data loading & Transformation
  • Data preprocessing & visualization
  • Extensible through plugins
  • Easy to use
  • No programming skills are required
  • 30-days Free plan
  • Studio (Professional): $7500 per year.
  • Studio (Enterprise): $15000 per year.
  • AI Hub: $54000 per year.

So above we have listed the best ML platforms and ML tools with all their features. We have also compared them respectively to make it easy for the readers. You might also want to check out the popular AI tools and frameworks that you must try. Still, have some queries? No worries, here we have answered the most common questions that readers ask.

Frequently Asked Questions

Which platform is best for machine learning?

Seeing the performance reviews on Gartner, we can say that KNIME is the first choice of customers who are looking for the best machine learning platform.

KNIME has also got 100% ‘Yes’ in the category of ‘Would Recommend’.

How do you explain data science and the best machine learning platform for beginners?

Data Science: Observing data to draw useful insights

Machine Learning Platform: It automates and speed-up the delivery lifecycle of prophetic apps that are capable of huge data processing.

If ML is in your mind to develop your next iOS application, then consult your ideas with us. Being one of the top app development companies, we have the right strategies for your business.

How can Machine Learning enhance my business?

Today, many businesses are experimenting with the increased use of AI and ML tools to transform their business and bring innovation to the work process. Here, you can see how ML improve your business:

  • Providing Personalized Customer Service
  • Data Visualization & KPI Tracking
  • Improved Finance Management
  • Innovate Marketing & Management


We hope that this information will help you to take the right action while selecting the best machine learning platform for your project. Our dedicated team of iOS developers is always committed to offer the best resolutions to your doubts.

The team understands the requirements of disruptive start-ups to large enterprises. Space-O Technologies is a leading machine learning consulting services provider, offering the best AI and ML development services.

In case, if you still have any queries or confusion with regards to machine learning software, what is the best platform for machine learning projects, then you can contact us. We will guide you further.

Bhaval Patel

Written by

Bhaval Patel is a Director (Operations) at Space-O Technologies. He has 20+ years of experience helping startups and enterprises with custom software solutions to drive maximum results. Under his leadership, Space-O has won the 8th GESIA annual award for being the best mobile app development company. So far, he has validated more than 300 app ideas and successfully delivered 100 custom solutions using the technologies, such as Swift, Kotlin, React Native, Flutter, PHP, RoR, IoT, AI, NFC, AR/VR, Blockchain, NFT, and more.