The team here at insideBIGDATA is deeply entrenched in keeping the pulse of the big data ecosystem of companies from around the globe. We’re in close contact with the movers and shakers making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what’s driving the success of our industry so we’re in a unique position to publish our quarterly IMPACT 50 List.
Big Data Industry Predictions for 2024
January 18, 2024 by 2 Comments
Welcome to insideBIGDATA’s annual technology predictions round-up! The big data industry has significant inertia moving into 2024. In order to give our valued readers a pulse on important new trends leading into next year, we here at insideBIGDATA heard from all our friends across the vendor ecosystem to get their insights, reflections and predictions for what may be coming. We were very encouraged to hear such exciting perspectives.
Book Review: The Kaggle Book/Workbook
June 23, 2023 by Leave a Comment
Kaggle is an incredible resource for all data scientists. I advise my Intro to Data Science students at UCLA to take advantage of Kaggle by first completing the venerable Titanic Getting Started Prediction Challenge, and then moving on to active challenges. Kaggle is a great way to gain valuable experience with data science and machine learning. Now, there are two excellent books to lead you through the Kaggle process. The Kaggle Book by Konrad Banachewicz and Luca Massaron published in 2022, and The Kaggle Workbook by the same authors published in 2023, both from UK-based Packt Publishing, are excellent learning resources.
Video Highlights: Yann LeCun and Andrew Ng: “AI Doomers” and Why the 6-month AI Pause is a Bad Idea
April 10, 2023 by Leave a Comment
In this Video Highlights feature, two respected industry luminaries, Andrew Ng and Yann LeCun, they discuss the proposal of a 6-month moratorium on generative AI. The discussion offers reasonable perspectives for how generative AI has turned the world on edge.
The $500mm+ Debacle at Zillow Offers – What Went Wrong with the AI Models?
December 13, 2021 by Leave a Comment
In this contributed article, Anupam Datta, Co-Founder, President, and Chief Scientist of TruEra, discusses Zillow and what went wrong with the AI models. For AI and ML models to perform for profitable outcomes, especially for high stakes models like Zillow’s, it is crucial to have serious AI governance supported by tools for monitoring and debugging, which includes having qualified humans-in-the-loop to adjust to major market shifts that can arise during unexpected events.
The Amazing Applications of Graph Neural Networks
June 26, 2021 by Leave a Comment
In this contributed article, editorial consultant Jelani Harper points out that a generous portion of enterprise data is Euclidian and readily vectorized. However, there’s a wealth of non-Euclidian, multidimensionality data serving as the catalyst for astounding machine learning use cases.
Infographic: The Rise of No-Code Development Platforms
January 1, 2021 by 2 Comments
Our friends over at Saas Platform company in Ireland called TeamKonnect have developed new infographic called “The Rise of No-Code Development Platforms” which is provided below. This infographic is a 101 guide to No-Code Development Platforms. Rising in popularity in the last decade, these platforms offer an exciting opportunity for businesses and organizations to develop apps that meet their needs without the engagement of software engineers.
The Difference Between Data Science and Data Analytics
June 3, 2017 by 11 Comments
In this contributed article, tech writer Rick Delgado, examines the differences between the terms: data science and data analytics, where people working in the tech field or other related industries probably hear these terms all the time, often interchangeably. Although they may sound similar, the terms are often quite different and have differing implications for business.
