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.

October 11, 2021 11 Oct'21
IBM introduces Environmental Intelligence Suite

The tech giant said the new software suite from its weather subsidiary will help organizations prepare for climate risk and weather disasters such as wildfires and flooding.
October 07, 2021 07 Oct'21
Machine learning development for autonomous vehicles

AI experts from the autonomous vehicle technology industry discuss automation, spotting flaws in and speeding up machine learning systems and accounting for changes in real time.
October 05, 2021 05 Oct'21
Dell introduces Validated Design for AI at VMworld 2021

The tech vendor revealed a new partnership with AI GPU maker Nvidia at VMWorld 2021 aimed at providing an AI and machine learning platform for IT users in virtualized environments.
September 15, 2021 15 Sep'21
Tableau and DotData partner on AI automation, visualization

Tableau and DotData partner to help data scientists and engineers accelerate machine learning automation while adding a visualization layer to model building.

Bring yourself up to speed with our introductory content

What is 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
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
fuzzy logic

Fuzzy logic is an approach to computing based on "degrees of truth" rather than the usual "true or false" (1 or 0) Boolean logic on which the modern computer is based. Continue Reading

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

How neural network training methods are modeled after the human brain

Training neural nets to mirror the human brain enables deep learning models to apply learning to data they've never seen before. Continue Reading
The top 5 benefits of AI in banking and finance

The strategic deployment of AI in banking and finance can bring substantial benefits. Learn about how AI tools are transforming financial services and the risks to be mindful of. Continue Reading
Top 9 types of machine learning algorithms, with cheat sheet

Machine learning can assist enterprises by quickly modeling large data sets. Choosing the right algorithm depends on the desired outcome and the makeup of your data science team. Continue Reading

Learn to apply best practices and optimize your operations.

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
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

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