Machine learning platforms

Enterprises need to make smart investments in machine learning platforms. With a range of features and price tags, making the right choice can seem like a daunting task. Discover machine learning platform comparison content, information on getting started with machine learning algorithms and best practices to gain the most from projects.

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Machine learning platforms News

January 06, 2020 06 Jan'20
U.S. restricts exports of geospatial AI software

The Trump administration's move to limit export of AI-based geospatial imaging software extends U.S. restrictions on technology that foreign countries could use to develop weapons systems.
December 12, 2019 12 Dec'19
DataRobot acquisition of Paxata adds data prep to AI platform

By buying data prep vendor Paxata, DataRobot plans to fill out its machine learning and AI platform with tools to automate data prep processes and provide an underlying data fabric.
November 07, 2019 07 Nov'19
Booz Allen releases Modzy AI platform and marketplace

Booz Allen Hamilton introduced an AI platform and marketplace made for uploading, deploying and managing AI models across a scalable environment.
November 04, 2019 04 Nov'19
Microsoft launches Azure Synapse Analytics for the cloud

New Microsoft Azure analytics service provides cloud BI and machine learning, enabling users to do analytics on data in various sources, including data warehouses and data lakes.

Machine learning platforms Get Started

Bring yourself up to speed with our introductory content

face detection

Face detection -- also called facial detection -- is an artificial intelligence (AI) based computer technology used to find and identify human faces in digital images. Continue Reading
The peaks and pitfalls of hyper-personalization marketing

As consumers begin to revolt against unlimited personal data collection and usage, the longevity of hyper-personalized communication may be cut short. Continue Reading
UX defines chasm between explainable vs. interpretable AI

From deep learning to simple code, all algorithms should be transparent. The frameworks of AI interpretability and explainability aim to make machine learning understandable to humans. Continue Reading

Evaluate Machine learning platforms Vendors & Products

Weigh the pros and cons of technologies, products and projects you are considering.

How stock market prediction using AI impacts the trading floor

Robo-advisors and stock monitoring bots are changing the way traders and investors take on the stock market. Continue Reading
Where are we with machine translation in AI?

Machine translation has received a boost from cutting-edge technology like deep learning but continues to struggle with the complexities and nuances of human languages. Continue Reading
Comparing semi-supervised machine learning vs. one-shot learning

Machine learning models require massive amounts of data -- labeled or unlabeled. Two new approaches are hoping to curtail the need for large data sets and overarching human interference. Continue Reading

Manage Machine learning platforms

Learn to apply best practices and optimize your operations.

Merging DevOps and machine learning requires restructuring

Companies that are restructuring in order to merge their traditional DevOps teams with their machine learning efforts to aid with accessibility need to include voices from multiple teams. Continue Reading
The future state of machine learning needs improved frameworks

Utilizing machine learning in the collection and processing of data would most likely lead to more widespread adoption of AI based on the technology. Continue Reading
AI in hiring gets companies more talent, faster

Through processes like automated candidate sourcing and candidate rediscovery, AI sifts through many resumes to find those most suited to a position. Continue Reading

Problem Solve Machine learning platforms Issues

We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.

How to create a data set for machine learning with limited data

A shortage of data for machine learning training sets can halt a company's AI development in its tracks. Turning to external sources and hidden data can solve the problem. Continue Reading
Brands must allay worries for AI in transportation to take hold

The personal mobility market is turning to emotional analysis and AI to negate fear and trepidation around emerging vehicle technology and the future of transportation. Continue Reading
Serverless machine learning reduces development burdens

Getting started with machine learning throws multiple hurdles at enterprises. But the serverless computing trend, when applied to machine learning, can help remove some barriers. Continue Reading