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10 Best Machine Learning Software [2022 List]

Machine learning (ML) is just one way that companies can transform how they use big data to best understand their customers’ behavior, satisfaction, and/or loyalty. ML can hunt for patterns and anomalies that users didn’t even think to query about for themselves. 

Some machine learning algorithms are pre-designed to specialize in one thing, but in this article, we are looking specifically at machine learning applications that enable the user to implement their own machine learning models for whatever data you have.

I will present some of the best machine learning tools and outline how users can best leverage each for deep learning, data mining, and dataset visualization.

What Is Machine Learning Software?

Machine learning software is any dedicated tool used for artificial intelligence, self-iteration based on data, unsupervised learning, and other ML classifiers. Much software at work today has elements of machine learning, like in email filtering and computer vision. 

There are also machine learning specialty software for things like simulation, recruitment, architecture, and accounting. Some ML toolkits, like the ones listed in this article, can be custom-built to adapt to your unique data sets and workflow needs.

The Best Machine Learning Software List

Here’s a shortlist of the best machine learning software:

  1. cnvrg.io

    Best machine learning software for the gaming industry

  2. Amazon Machine Learning

    Best for those in the AWS ecosystem

  3. H2O.ai

    Best open source integration with Spark

  4. TensorFlow

    Best for ML models on mobile and IoT devices

  5. IBM Machine Learning

    Best free, open-source machine learning software

  6. Neural Designer

    Best for their high GPU training speed

  7. Torch

    Best for linear algebra routines

  8. Google Cloud AI Platform

    Best low- and no-code machine learning framework

  9. Spell

    Best machine learning software for collaborative teamwork

  10. Anaconda

    Best machine learning software for small businesses and freelancers

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

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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.

1

cnvrg.io

Best machine learning software for the gaming industry

Cnvrg.io 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. Cnvrg.io offers industry-specific assistance for the gaming industry, such as the optimization of monetization, churn reduction, and in-game experience personalization.

Cnvrg.io costs from $9500/instance and offers a free 14-day trial. They also offer a free version of their platform called CORE.

Pros:

Works with any framework or programming language

Excellent free-to-use options

Releases industry-first dataset caching for ML

Good for hybrid machine learning

Cons:

Over 3000 jobs/year will require their Premium edition

Feature-set is still a work in progress, as they are new to the market

Better for SMB rather than large enterprises

14 Days Free Trial

$9500/instanc

2

Amazon Machine Learning

Best for those in the AWS ecosystem

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.

Pros:

Easily handles large datasets using multiple servers

Powerful auto-scaling model server

Visually track development of ML modules

Customizations are easy to adjust and modify

Cons:

Best for those already in the Amazon ecosystem

Advanced programming background required

Cannot schedule training jobs at this time

12-month free trial

$0.42/hour

3

H2O.ai

Best open source integration with Spark

H2O.ai is a user-friendly, accessible AI platform that was named a Visionary by Gartner in the 2020 Magic Quadrant for Data Science and Machine Learning Platforms. Fraud prevention, anomaly detection, and price optimization are some items they offer. H2O Sparkling Water integrates with Spark for users who want to make a query using Spark SQL, feed the results into H2O to build a model and make predictions, and then use the results again in Spark.

H2O.ai costs from $0.046/hour and offers a free 21-day trial.

Pros:

Big data support with H2O’s Sparkling Water

Flexible modeling including Ensemble

Flexible horizontal scaling via provisioning dynamic clusters

Excellent commitment to open-source transparency

Cons:

More cutting-edge algorithms would be welcome

Some documentation could be refined

Charting and visuals could use a

21 Days Free Trial

$0.046/hour

4

TensorFlow

Best for ML models on mobile and IoT devices

TensorFlow boasts easy model building that can be customized to address image reading and classification, buyer and seller experience optimization, mobile proof-of-purchase elements, job completion predictions, and more. Plus, they offer a deep learning framework for on-device inference. Users can pick a new or retrained ML model, convert it to a compressed flat buffer, and easily load the resulting .tflite file into any mobile or embedded device.

TensorFlow is free to use.

Pros:

Streamlined, user-friendly training and debugging process

Completely free to use

Huge library of functions for tasks around text, images, tabular, video, etc.

Multi-GPU support with simple, clear documentation

Cons:

Some error messages are convoluted/hard to understand

Not ideal for build tools with poor Python support

Better bindings with the JVM would be welcome

5

IBM Machine Learning

Best free, open-source machine learning software

The IBM Machine Learning suite lets you mix and match between a few different products, like IBM Watson Studio, IBM Watson Machine Learning, IBM Watson OpenScale, and IBM Cloud Pak for Data. Users are able to build AI models using open source tools, deploy AI models with your apps, and monitor AI models. IBM Machine Learning also has a robust free lite plan for 20 CUH and a maximum of 2 parallel decision optimization batch jobs per deployment.

IBM Machine Learning costs from $0.50/CUH and offers a free lite plan with 20 capacity unit-hours. Paid plans also offer a free 30-day trial.

Pros:

Drag-and-drop data prep, blending, and modeling

Text analytics for unstructured data

Unlimited modeling without overages

Well documented, easy-to-use API

Cons:

Must launch each service in separate tabs (no single overview)

Implementation journey is a time commitment

Some restrictions when adjusting results and parameters while training models

30 Days Free Trial

$0.50/CUH and offers a free lite plan with 20 capacity unit-hours

6

Neural Designer

Best for their high GPU training speed

Neural Designer is a high-performance machine learning platform that lets you skirt writing code and building block diagrams with a series of drag-and-drop, point-and-click tools. They boast an average GPU training speed of 417K+ samples per second, which is faster than many competing platforms. Neural Designer is entirely programmed in C++, which sacrifices some ease of use qualities but offers better performance speeds instead.

Neural Designer costs from $2495/user/year and offers a free analysis of up to 1,000 data rows.

Pros:

Excellent presentation of data processing results

Handles parameter optimization problems well

Good memory management for importing big data sets

Fast calculations using CPU and GPU optimization

Cons:

No cloud-based tool at this time

Inflexible pricing plan

Some limitations around automating processes

Free analysis of up to 1,000 data rows.

$2495/user/year

7

Torch

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. Pros: *Opensource, *Pre-trained models lets you develop neural networks faster, *Easy to use, *Highly flexible , *Fast (no compile time needed) and efficient GPU support Cons: *Need to know or learn Lua scripting language, *Need LuaRocks package manager, can’t write in Python

8

Google Cloud AI Platform

Best low- and no-code machine learning framework

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.

Pros:

AI explanations and What-If validation testing

Very easy to use interface

Good connection with TPUs and TensorFlow

Good out-of-the-box CV algorithms and video processing modules

Cons:

Not well suited for hybrid cloud deployments

Additional library support would be welcome

Limited to running 25 models in parallel

offers a free $300 credit for your first 90 days.

$0.19/hour

9

Spell

Best machine learning software for collaborative teamwork

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.

Pros:

Intuitive tools and simple commands

Excellent command-line interface and usability

Takes care of infrastructure for quick-start projects

Cons:

Free version runs only on their shared community cluster

Models need to run with Python

freemium version with $10 of GPU credit

$329/user/month

10

Anaconda

Best machine learning software for small businesses and freelancers

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.

Pros:

Robust open-source freeware package

Good management of custom environments

Friendly with different versions of Python and its libraries

Pre-installs the most useful libraries and packages at the get-go

Cons:

Integration with Git/versioning software would be an improvement

Source-controlled environments and custom repositories limited to Enterprise Edition

Excludes PyCharm, Atom, and Docker

The 10 Best Machine Learning Software Summary

Tool Free Option Price
1
cnvrg.io

Best machine learning software for the gaming industry

14 Days Free Trial

$9500/instanc Visit Website
2
Amazon Machine Learning

Best for those in the AWS ecosystem

12-month free trial

$0.42/hour Visit Website
3
H2O.ai

Best open source integration with Spark

21 Days Free Trial

$0.046/hour Visit Website
4
TensorFlow

Best for ML models on mobile and IoT devices

Not available

Visit Website
5
IBM Machine Learning

Best free, open-source machine learning software

30 Days Free Trial

$0.50/CUH and offers a free lite plan with 20 capacity unit-hours Visit Website
6
Neural Designer

Best for their high GPU training speed

Free analysis of up to 1,000 data rows.

$2495/user/year Visit Website
7
Torch

Best for linear algebra routines

Not available

Visit Website
8
Google Cloud AI Platform

Best low- and no-code machine learning framework

offers a free $300 credit for your first 90 days.

$0.19/hour Visit Website
9
Spell

Best machine learning software for collaborative teamwork

freemium version with $10 of GPU credit

$329/user/month Visit Website
10
Anaconda

Best machine learning software for small businesses and freelancers

Not available

Visit Website

Need expert help selecting the right Machine Learning Software?

We’ve joined up with the software comparison platform Crozdesk.com to assist you in finding the right software. Crozdesk’s Machine Learning Software advisors can create a personalized shortlist of software solutions with unbiased recommendations to help you identify the solutions that best suit your business’s needs. Through our partnership you get free access to their bespoke software selection advice, removing both time and hassle from the research process.

It only takes a minute to submit your requirements and they will give you a quick call at no cost or commitment. Based on your needs you’ll receive customized software shortlists listing the best-fitting solutions from their team of software advisors (via phone or email). They can even connect you with your selected vendor choices along with community negotiated discounts. To get started, please complete the form below:

Other Machine Learning Software

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

  1. Torch – Best for linear algebra routines
  2. Weka – Best for image and text classification
  3. TADA Artificial Intelligence – Best for small data
  4. Kount – Best for bots and account takeover fraud

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.

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