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.

June 09, 2021 09 Jun'21
DataRobot integrates AI modeling tools with Snowflake

The AI vendor and cloud data warehouse vendors' latest collaboration will enable joint customers to develop and deploy AI models with fewer production lags.
June 03, 2021 03 Jun'21
L'Oréal to 'revolutionize' beauty services using Google Vertex

ModiFace says it will save many hours developing AI algorithms by exploiting the compute power and AI tools of Google Vertex to create digitized beauty services.
May 27, 2021 27 May'21
Databricks steps up in competitive machine learning market

At its Data + AI Summit, Databricks introduced AutoML, glass box tools and Delta Lake-based Feature Store capabilities for its AI platform.
May 25, 2021 25 May'21
Affectiva emotion AI vendor latest in AI acquisition wave

Amid a surging market for AI technology, Smart Eye, a vendor of AI-based eye tracking and driver tracking systems, acquires a vendor of emotion-sensing AI software.

Bring yourself up to speed with our introductory content

artificial intelligence

Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision. Continue Reading
narrow AI (weak AI)

Narrow AI is an application of artificial intelligence technologies to enable a high-functioning system that replicates -- and perhaps surpasses -- human intelligence for a dedicated purpose. Continue Reading
How do big data and AI work together?

Enterprises are leaning on big data to train AI algorithms and, in turn, are using AI to understand big data. The results are pushing operations forward. Continue Reading

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

9 top AI and machine learning trends for 2021

Tiny ML, multi-modal learning, responsible AI -- learn about the top trends in AI for 2021 and how they promise to transform how business gets done. Continue Reading
AI vs. machine learning vs. deep learning: Key differences

AI terms are often used interchangeably, but they are not the same. Understand the difference between artificial intelligence, machine learning and deep learning. Continue Reading
4 main types of artificial intelligence: Explained

AI technology can exceed human performance in many areas, but it is still no match for the human brain. Learn about the four main types of AI. Continue Reading

Learn to apply best practices and optimize your operations.

How to detect bias in existing AI algorithms

While enterprises can't eliminate bias from their data, they can significantly reduce bias by establishing a governance framework and employing more diverse employees. Continue Reading
How to build a machine learning model in 7 steps

Building a viable, reliable and agile machine learning model that streamlines operations and bolsters business planning takes patience, preparation and perseverance. Continue Reading
Unsupervised machine learning: Dealing with unknown data

Learn how machine learning works when dealing with unclassified, unlabeled data sets and how, using certain algorithms and other practices, the system can learn on its own. Continue Reading

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

Discover 2 unsupervised techniques that help categorize data

Two unsupervised techniques -- category discovery and pattern discovery -- solve ML problems by seeking similarities in data groups, rather than a specific value. Continue Reading
Combating racial bias in AI

By employing a diverse team to work on AI models, using large, diverse training sets, and keeping a sharp eye out, enterprises can root out bias in their AI models. Continue Reading
Tackling the AI bias problem at the origin: Training data

Though data bias may seem like a back-end issue, the enterprise implications of an AI software using biased data can derail model implementation. Continue Reading