Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
Data Science Bows Before Prompt Engineering and Few Shot Learning
March 13, 2023 by 1 Comment
In this contributed article, editorial consultant Jelani Harper takes a new look at the GPT phenomenon by exploring how prompt engineering (stores, databases) coupled with few shot learning can constitute a significant adjunct to traditional data science.
Video Highlights: Copilot for R
March 11, 2023 by Leave a Comment
Our video highlights selection for today is by data science industry luminary David Smith who made a presentation to the NYC Data Hackers on the topic of Copilot for R. If you haven’t come across Copilot before, it’s like an AI-based pair programmer that suggests new lines of code, and perhaps entire functions, based on context.
TOP 10 insideBIGDATA Articles for February 2023
March 10, 2023 by Leave a Comment
In this continuing regular feature, we give all our valued readers a monthly heads-up for the top 10 most viewed articles appearing on insideBIGDATA. Over the past several months, we’ve heard from many of our followers that this feature will enable them to catch up with important news and features flowing across our many channels.
Heard on the Street – 3/8/2023
March 8, 2023 by Leave a Comment
Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
insideBIGDATA Latest News – 3/7/2023
March 7, 2023 by Leave a Comment
In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday. Fortunately, we’re in close touch with vendors from this vast ecosystem, so we’re in a unique position to inform you about all that’s new and exciting. Our massive industry database is growing all the time so stay tuned for the latest news items describing technology that may make you and your organization more competitive.
Heard on the Street – 3/1/2023
March 1, 2023 by 2 Comments
Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
“Above the Trend Line” – Your Industry Rumor Central for 2/28/2023
February 28, 2023 by Leave a Comment
Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.
Data Science 101: The Data Science Process
February 27, 2023 by Leave a Comment
Welcome to insideBIGDATA’s Data Science 101 channel brining you perspectives for the topics of the day in data science, machine learning, AI and deep learning. Many of the video presentations come from my lectures for my Introduction to Data Science class I teach at UCLA Extension. In today’s slide-based video presentation I discuss The Data Science Process, an overview of the steps that data scientists use solving problems with data science and machine learning technologies.
Book Review: Tree-based Methods for Statistical Learning in R
February 23, 2023 by Leave a Comment
Here’s a new title that is a “must have” for any data scientist who uses the R language. It’s a wonderful learning resource for tree-based techniques in statistical learning, one that’s become my go-to text when I find the need to do a deep dive into various ML topic areas for my work. The methods […]
