Machine learning modeling

There are a number of ways to tackle machine learning modeling. Find content on supervised and unsupervised machine learning algorithm training and modeling processes, including expert tips to help you evaluate, choose and use the right machine learning model to deliver accurate predictive outputs to solve business problems.

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August 13, 2018 13 Aug'18
O'Reilly machine learning survey: Enterprises aim for maturity

A new survey finds companies are using fairness and bias as metrics to evaluate the success of a machine learning model.
July 27, 2018 27 Jul'18
BigQuery ML moves machine learning into Google BigQuery

Google is enabling BigQuery users to build SQL-based machine learning models inside the cloud data warehouse via a BigQuery ML technology now out in beta.
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.

Bring yourself up to speed with our introductory content

AI for education brings benefits to burdened school staff

Using AI in education can have a dramatic impact on the way teachers use their time and the manner in which students are served individually. Expect the trend to continue. Continue Reading
artificial neural network (ANN)

In information technology (IT), a neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain. 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

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

What do businesses do with the top machine learning platforms?

Take a deep dive into machine learning, including decision trees, clustering, reinforced learning, neural networks, as well as supervised and unsupervised machine learning. Continue Reading
How to find the best machine learning frameworks for you

There's no shortage of open source deep learning tools today, and evaluating them can be a challenge. But there are some primary considerations to keep in mind. 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

Learn to apply best practices and optimize your operations.

Machine learning in production challenges developers' skills

Deploying machine learning models requires an entirely different skill set than developing them, and data scientists and engineering teams need to be ready to bridge this gap. Continue Reading
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

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

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