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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June 19, 2018 19 Jun'18
AI can reduce workplace bias, says CEO of leading HR group

AI technology may help HR reduce workplace bias, according to Johnny Taylor, president and CEO of the Society for Human Resource Management, an HR organization that has 300,000 members.
June 08, 2018 08 Jun'18
Databricks platform additions unify machine learning frameworks

Databricks' new products take aim at simplifying machine learning integration -- something that has become increasingly difficult, as the number of tools has multiplied.
April 16, 2018 16 Apr'18
How IBM's data science team quickens users' AI projects

In this Q&A, IBM's Seth Dobrin discusses the rising user interest in machine learning and AI projects and the help inexperienced users need to launch those projects.
March 02, 2018 02 Mar'18
AI experts advise developers on dev tools

New tools help developers build better, smarter AI apps, as machine learning toolkits have progressed exponentially over the last few years.

Bring yourself up to speed with our introductory content

Develop smart AI in CRM strategies to win and keep customers

Of the three words that comprise customer relationship management, one word binds the other two. As necessity and competition dictate that CRM upgrade itself with artificial intelligence and flights to the cloud, what counts most in ... Continue Reading
cognitive modeling

Cognitive modeling is an area of computer science that deals with simulating human problem-solving and mental processing in a computerized model. Continue Reading
Machine learning still big at Stripe despite deep learning hype

Classical machine learning methods are getting overshadowed in today's AI landscape, but problems with deep learning are keeping them relevant at payment processor Stripe. Continue Reading

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

Data scientist vs. business analyst: What's the difference?

Data science and business analyst roles differ in that data scientists must deep dive into data and come up with unique business solutions -- but the distinctions don't end there. Continue Reading
Getting to machine learning in production takes focus

Bridging the gap between training and production is one of the biggest machine learning development hurdles enterprises face, but some are finding ways to streamline the process. Continue Reading
CTO Simon Crosby explains edge intelligence, talks AI uses and risks

Edge intelligence is the newborn child of edge analytics and machine learning. In this podcast, CTO Simon Crosby explains the tech and discusses AI uses, data breaches and more. Continue Reading

Learn to apply best practices and optimize your operations.

How one company thinks chatbots and AI can change insurance

Insurance agency management company In-Fi is hoping AI chatbots can streamline homeowner insurance applications and bring the process in line with customers' expectations. Continue Reading
Why machine learning models require a failover plan

Flawed machine learning models lead to failures and user interruptions. Expert Judith Myerson explains the causes for failures and how a failover plan can improve user experience. Continue Reading

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AI for the enterprise transmitted directly from Mars

For marketing intelligence to explore new frontiers and achieve its ultimate goal, chief marketing officers may find their CRM applications were once developed by NASA and tested in space. Continue Reading
GDPR regulations put premium on transparent AI

As the EU's GDPR regulations go into effect, enterprises must focus on building transparency in AI applications so that algorithms' decisions can be explained. Continue Reading
Machine vision makes paper a thing of the past for insurers

The insurance industry is buried in paper-based processes. Former MetLife CIO Gary Hoberman aims to change that with a platform that runs on AI and machine vision. Continue Reading