14 Best Machine Learning Software [2023 List]

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.

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.

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.

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.

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.

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.

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.

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

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.

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.