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RStudio is a modular data science platform, combining open source and commercial products. The vendor states their open source offerings, such as the RStudio IDE, Shiny, rmarkdown and the many packages in the tidyverse, are used by millions of data scientists around the world to…
IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies…
The DataRobot AI Cloud platform is presented as a solution that accelerates and democratizes data science by automating the end-to-end journey from data to value and allows users to deploy AI applications at scale. DataRobot provides a centrally governed platform that gives users…
Jupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and…
Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data…
TensorFlow is an open-source machine learning software library for numerical computation using data flow graphs. It was originally developed by Google.
Oracle Machine Learning (formerly Oracle Advanced Analytics) combines the Oracle database with Oracle Data Miner and SQL as well as R programming language functionality, providing a complete predictive analytics suite.
OpenText Magellan Analytics Suite leverages a comprehensive set of data analytics software to identify patterns, relationships and trends through data visualizations and interactive dashboards.
Google Cloud AI provides modern machine learning services, with pre-trained models and a service to generate tailored models.
Amazon SageMaker enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.
Plotly headquartered in Montreal creates data visualization and UI tools for ML, data science, engineering, and the sciences with language support for Python, R, Julia, and JS. Plotly's Dash aims to empower teams to build data science and ML apps that put Python, R, and Julia in…
IBM offers Watson Discovery, a natural language processing (NLP) application with options to measure sentiment, detect entities, semantic roles, and other concepts.
Microsoft's Azure Machine Learning is and end-to-end data science and analytics solution that helps professional data scientists to prepare data, develop experiments, and deploy models in the cloud. It replaces the Azure Machine Learning Workbench.
Cloudera Data Platform (CDP), launched September 2019, is designed to combine the best of Hortonworks and Cloudera technologies to deliver an enterprise data cloud. CDP includes the Cloudera Data Warehouse and machine learning services as well as a Data Hub service for building custom…
IBM offers Watson Visual Recognition, a machine learning application designed to tag and classify image data, and deployable for a wide variety of purposes.
Amazon TensorFlow enables developers to quickly and easily get started with deep learning in the cloud.
Machine learning tools are algorithmic applications of artificial intelligence that give systems the ability to learn and improve without ample human input; similar concepts are data mining and predictive modeling. They allow software to become more accurate in predicting outcomes without being explicitly programmed. The idea is that a model or algorithm is used to get data from the world, and that data is fed back into the model so that it improves over time. It’s called machine learning because the model “learns” as it is fed more and more data.
They can be used, for example, to build recommendation engines, predict search patterns, filter spam, build news feeds, detect fraud and security threats, and much more. There are four types of machine learning algorithms: supervised, unsupervised, semi-supervised, and reinforced.
Supervised algorithms are machine learning tools with training wheels. They require a person to program both the input and the desired output, as well as provide feedback as to the accuracy of the end results.
Unsupervised algorithms require very little human intervention by instead using an approach called “deep learning” to review massive banks of data and arrive at conclusions based on previous examples of training data; they are, therefore, generally used for more complex processing tasks such as image recognition, speech-to-text, and natural language generation.
Semi-supervised algorithms tend to fall in the middle ground.
Reinforced algorithms force models to repeat a process until it produces the most favorable outcomes. Attempts that produce these favorable outcomes are rewarded and attempts that produce unfavorable results are penalized until the algorithm learns the optimal process.
Most vendors offering machine learning tools include:
Some vendors also offer additional tools to
When beginning your process for a machine learning tool with which to get started, walk through the following flow of questions to help you narrow down your options:
Ready to start comparing your shortlist head-to-head? Start a Machine Learning Tools comparison
Many vendors offering machine learning tools will offer a free trial or a free version with a limited batch of predictions. There are several free and open-source machine learning platforms, like Google's Tensorflow, for developers on a budget. For paid plans, prices are generally Pay-As-You-Go, tiered by price per hour and training units, typically starting at $0.10/Unit/Hour. Deep learning capabilities are typically more expensive, at $1+/GPU/Hour.
