Big data and machine learning

Big data and machine learning is a powerful pair for data-driven enterprises. Data collection and storage using big data frameworks, data integration and data preparation can be difficult for even the most experienced data scientists. Get expert insights and best practices for working with big data and machine learning projects.

September 17, 2020 17 Sep'20
Rivals Cloudian, Scality embrace all-flash object storage

Primarily used as a disk repository, object storage use cases are evolving to support workloads that need fast flash. Rivals Cloudian and Scality provide the latest evidence.
August 17, 2020 17 Aug'20
Does technology increase the problem of racism and discrimination?

According to a publication from the MIT Technology Review, technology promotes racism. Most facial recognition algorithms discriminate against the Black population. And even certain concepts or technological terminology tend to be offensive, ...
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.

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Do you have competitive data science key skills?

Data scientists should be familiar with a variety of programming languages, machine learning algorithms and databases and must be able to communicate these skills across teams. Continue Reading
predictive modeling

Predictive modeling, also called predictive analytics, is a mathematical process that seeks to predict future events or outcomes by analyzing patterns that are likely to forecast future results. Continue Reading
3 machine learning best practices to use in IoT projects

IoT machine learning takes a whole team of experts that can approach the project with the right mindset, effectively communicate, and facilitate user feedback and testing. Continue Reading

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

KDD in data mining assists data prep for machine learning

While data scientists are often familiar with data mining, the deeper knowledge discovery in databases (KDD) procedure can help prepare data to train machine learning algorithms. Continue Reading
AI in security analytics is the enhancement you need

AI-powered analytics is critical to an effective, proactive security strategy. Learn how AI-enabled tools work and what your organization needs to do to reap their benefits. Continue Reading
AI in cybersecurity ups your odds against persistent threats

AI capabilities can identify and take down cyberthreats in real time but are only part of what your team needs to come out on the winning side of the cybersecurity battle. Continue Reading

Learn to apply best practices and optimize your operations.

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
Speech to text for deaf users aids in accessibility

For the millions of people who are hard of hearing, speech-to-text advancements have improved their ability to complete daily tasks -- but the tech still has a long way to go. Continue Reading
AI cybersecurity raises analytics' accuracy, usability

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

9 data quality issues that can sideline AI projects

The quality of your data affects how well your AI and machine learning models will operate. Getting ahead of these nine data issues will poise organizations for successful AI models. Continue Reading
How to troubleshoot 8 common autoencoder limitations

Autoencoders' ability for automated feature extraction, data preparation, and denoising are complicated by their common problems and limitations in usage. Continue Reading
Data science's ongoing battle to quell bias in machine learning

Machine learning expert Ben Cox of H2O.ai discusses the problem of bias in predictive models that confronts data scientists daily and his techniques to identify and neutralize it. Continue Reading