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With so many different machine learning software available, figuring out which is right for you is tough. You know you want to create models that can analyze complex data sets and perform a wide array of tasks but need to figure out which tool is best. I've got you! In this post I'll help make your choice easy, sharing my personal experiences using dozens of different machine learning tools with various projects, with my picks of the best machine learning software.

What Is Machine Learning Software?

Machine learning software comprises a range of applications and platforms that facilitate the development, training, and implementation of machine learning models. These tools enable computers to learn from and make predictions or decisions based on data, using algorithms and statistical models. They are used in various domains for tasks like data analysis, pattern recognition, predictive modeling, and natural language processing.

The benefits and uses of machine learning software include enhancing data-driven decision-making, automating complex analytical tasks, and providing insights that may not be immediately apparent. They allow for more accurate predictions and efficient pattern recognition, leading to innovations in personalization, operational efficiency, and problem-solving across diverse fields. This software is instrumental in transforming large datasets into actionable intelligence, driving efficiency and innovation in businesses and research.

Overviews Of The 10 Best Machine Learning Software

Here’s a brief description of each machine learning platform on my list showing what it does best, plus screenshots to showcase some of the features.

Best for automating the ML workflow

  • 14-day free trial
  • Pricing upon request
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Rating: 4.8/5

The Iguazio MLOps Platform is a comprehensive tool designed to automate and accelerate the machine learning workflow, allowing for a smooth transition from development to deployment. It offers features such as the ability to ingest data from any source and type, train and evaluate models at scale, and deploy models with ease to an operational pipeline. The platform also provides monitoring capabilities to detect drift and auto-trigger retraining, as well as integrated CI/CD across code, data, and models. This tool can serve innovation across a wide range of industries.

Inguazio offers a 14-day trial with pricing available upon request.

Best machine learning software for small businesses and freelancers

  • Free plan available
  • From $9/month
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Rating: 4.6/5

Anaconda is a hearty platform for the MLOps life cycle, and is used by the likes of American National Bank, AT&T, Toyota, and Goldman Sachs. Standard features include a Conda package manager, unlimited commercial packages and bandwidth, a mirrored or cloud-based repository, and an environment manager. Their Individual subscription tier is perfect for freelancers: free to use, thousands of open-source packages and libraries, and 7500+ Conda packages.

Anaconda costs from $14.95/mo and also offers a free Individual Edition.

Best for real-time AP automation

  • 15-day free trial
  • Pricing upon request
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Rating: 4.4/5

Yooz is a cloud-based financial software that provides an automated accounts payable solution, utilizing artificial intelligence and machine learning to facilitate the capture, processing, and management of invoices. The platform is designed to assist businesses in reducing manual tasks associated with invoice handling by offering features such as intelligent data capture, automated workflow for invoice approval, and electronic payment processing. Yooz also integrates with a variety of ERP and accounting systems, enabling synchronized financial operations and data accuracy. 

Yooz offers pricing upon request. A 15-day free trial is also available.

Best machine learning software for the gaming industry

  • 14 Days Free Trial
  • $9500/instanc
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Rating: 5/5 is a scalable full-stack solution for MLOps and model management. They are a leading data science platform with collaborative ML environments, container-based infrastructure, and production-ready infrastructure with native Kubernetes cluster orchestration. offers industry-specific assistance for the gaming industry, such as the optimization of monetization, churn reduction, and in-game experience personalization. costs from $9500/instance and offers a free 14-day trial. They also offer a free version of their platform called CORE.

Best for linear algebra routines

Torch is an open source scientific computing framework used for creating machine learning algorithms or neural networks. Unlike NumPy, it prioritizes GPU support. Torch is efficient and easy to use—it uses LuaJIT as a scripting language, which allows it to interface with C/CUDA seamlessly.

Torch is open source and free to use.

Best machine learning software for collaborative teamwork

  • freemium version with $10 of GPU credit
  • $329/user/month

Spell specializes in building and managing machine learning projects in high-impact, changing environments. Users can easily distribute their code to run projects in parallel, deploy models in Kubernetes-based infrastructure, and access collaborative Jupyter workspaces and resources. They have simple set-up and onboarding features for shifting and growing teams, including intuitive web console tools and simple command line tools.

Spell costs from $329/user/month and also offers a freemium version with $10 of GPU credit.

Best for free add-on products and connectors

  • offers 12 months free with a $200 credit for the first 30 days.
  • $0.333/hour

Microsoft’s Azure Machine Learning lets users quickly and easily build, train, and deploy machine learning models. QA leads will enjoy being able to employ automated machine learning that more quickly identifies suitable algorithms and hyperparameters. Many of their accentuating services are free forever, including certain app services, event processing, and automation for up to 500 minutes of job runtime.

Azure Machine Learning costs from $0.333/hour and offers 12 months free with a $200 credit for the first 30 days.

Best for those in the AWS ecosystem

  • 12-month free trial
  • $0.42/hour

Amazon Machine Learning empowers users to build, deploy, and run machine learning applications in the cloud through AWS. Your team will be able to tap into continuously trained and fully managed natural language processing (NLP), deep learning-based image recognition, and a flexible allotment of t2.medium notebook usage per month. Single-click processes and preset versioning rules make getting things running quick and easy.

Amazon Machine Learning costs from $0.42/hour and offers a 12-month free trial.

Best for image and text classification

  • Free To Use

Weka is a collection of Java-based machine learning algorithms used for data mining. It provides a variety of tools for data preparation, classification, clustering, regression, association rules mining, and visualization. Weka is well-suited to developing new machine learning and deep learning schemes.Weka is open source and free to use. Pros: *Opensource, *Easy to learn & implement, *Rapid exploratory data analysis, *Platform-agnostic on machines that run Java Cons:Low graphics quality, Outdated/clunky UI

Best low- and no-code machine learning framework

  • offers a free $300 credit for your first 90 days.
  • $0.19/hour

Google Cloud AI platform brings together its AI Platform, AutoML, and MLOps for a comprehensive and unified experience. Their platform scales to the user’s skill level, offering both point-and-click data science using AutoML as well as advanced model optimization. They provide both code-based and no-code tools for a simplified machine learning experience.

Google Cloud AI Platform costs from $0.19/hour and offers a free $300 credit for your first 90 days.

The Best Machine Learning Software Summary

Tools Price
iguazio Pricing upon request
Anaconda From $9/month
Yooz Pricing upon request $9500/instanc
Torch No price details
Spell $329/user/month
Azure Machine Learning $0.333/hour
Amazon Machine Learning $0.42/hour
Weka No price details
Google Cloud AI Platform $0.19/hour
Preview Image - <h2 class="c-block__title b-summary-table__title c-listicle__title h3" > Compare Software Specs Side by Side</h2>

Compare Software Specs Side by Side

Use our comparison chart to review and evaluate software specs side-by-side.

Compare Software

Other Machine Learning Software

Here’s a few more that didn’t make the top list.

  1. TensorFlow

    Best for ML models on mobile and IoT devices


    Best open source integration with Spark

  3. Neural Designer

    Best for their high GPU training speed

  4. IBM Machine Learning

    Best free, open-source machine learning software

  5. Pecan

    Best machine learning software for predictive customer analytics

  6. Kount

    Best for bots and account takeover fraud

  7. TADA Artificial Intelligence

    Best for small data

Machine Learning Software Comparison Criteria

Here’s a summary of my evaluation criteria: 

  1. User Interface (UI): Does the software provide clean and attractive data processing and data analytics tools? Are large-scale computations presented in a way that enables easy drill-downs?
  2. Usability: Does the software work seamlessly with different programming languages and every popular machine learning library? Do advanced features offer tutorial help either on the company's website or as in-app wizards?
  3. Integrations: Does the ML software connect easily with other popular programming tools and ML libraries like Java, Apache Mahout and Apache Spark, Hadoop, Keras, Pytorch, and Scikit-learn?
  4. Value for $: How appropriate is the price for the features, capabilities, and use case? Do they offer easy, flexible scaling by Capacity Unit-Hour (CUH)?

Machine Learning Software Key Features

  1. Pattern recognition, classification, and regression
  2. Predictive analytics
  3. Dimensionality reduction functionality 
  4. Support vector machines
  5. Connection with popular machine learning libraries, such as Apache Spark MLlib 
  6. Works with key programming languages (Scala, Java, C++, R, Python, etc.)
  7. End-to-end open-source machine learning

Which Machine Learning Software Have You Used?

What machine learning software do your data scientists use? What tools do you use to optimize your training data and craft ideal neural networks? What are your best tips for real-time data analysis and data preparation? What ML models are your go-to? Sound off in the comments!

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By Jason Boog

Over his 15-year career, Jason Boog has worked as a QA tester, QA analyst, and Senior QA Analyst on video games, commercial sites, and interactive web applications. He spent more than a decade building out the QA team and process as Director of Quality & Client Support at a full-service digital agency.