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.

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.
April 14, 2021 14 Apr'21
Data scientist shortage leaves organizations uncertain

Despite their desire to use data science in their decision-making process, some organizations can't find qualified data scientists to develop and run their data science initiatives.
March 30, 2021 30 Mar'21
Fungible computational storage eyes composable use cases

Fungible's computational storage anchors a new offering for composable infrastructure. The Fungible Data Center license allows IT teams to consume resources on demand.
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.

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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.

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
8 big data use cases for businesses and industry examples

As the understanding of big data requirements increases, so do big data use cases. Here are eight ways businesses are using big data to improve operations. 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