Welcome to insideBIGDATA’s Data Science 101 channel bringing 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 Venn Diagram, a subject-by-subject overview of the constituent parts of the discipline of data science.
Heard on the Street – 4/27/2023
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 4/26/2023
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.
Power to the Data Report: Introduction to Neural Magic
Neural Magic is a startup company that focuses on developing technology that enables deep learning models to run on commodity CPUs rather than specialized hardware like GPUs. The company was founded in 2018 by Alexander Matveev, a former researcher at MIT, and Nir Shavit, a professor of computer science at MIT. They raised a total of $50 million in funding to date over 3 rounds, from investors such as Comcast Ventures, NEA, Andreessen Horowitz, Pillar VC, and Amdocs.
Heard on the Street – 4/20/2023
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 – 4/18/2023
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.
The insideBIGDATA IMPACT 50 List for Q2 2023
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.
Deloitte Launches Generative AI Practice to Help Clients Harness the Power of Disruptive New AI Technology
Deloitte announced a new practice designed to help clients harness the power of Generative AI and Foundation Models to exponentially enhance productivity and accelerate the pace of business innovation. The new practice combines the world-class services, AI talent and deep industry experience that enterprise leaders need as they design their Generative AI strategies and leverage the disruptive new technology to create innovative AI-fueled applications.
Heard on the Street – 4/13/2023
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.
Book Review: Math for Deep Learning
One of my favorite learning resources for gaining an understanding for the mathematics behind deep learning is “Math for Deep Learning” by Ronald T. Kneusel from No Starch Press. If you’re interested in getting quickly up to speed with how deep learning algorithms work at a basic level, then this is the book for you.