Sign up for our newsletter and get the latest big data news and analysis.

Machine Learning in Finance: Challenges, Successes & Opportunities

AI or machine learning is changing the way industries across the spectrum interact with their customers, as well as develop their processes. And nowhere is this more evident than in the financial business. Download a new insideHPC special report that explores the benefits, challenges and considerations involved with adopting machine learning in finance.

Quadcopter Navigation in the Forest using Deep Neural Networks

In the video presentation below, a group of deep learning researchers study the problem of perceiving forest or mountain trails from a single monocular image acquired from the viewpoint of a robot traveling on the trail itself. Previous literature focused on trail segmentation, and used low-level features such as image saliency or appearance contrast; the team proposes a different approach based on a Deep Neural Network used as a supervised image classifier.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – December 2017

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.

Top 5 Mistakes When Writing Spark Applications

In the presentation below from Spark Summit 2016, Mark Grover goes over the top 5 things that he’s seen in the field that prevent people from getting the most out of their Spark clusters. When some of these issues are addressed, it is not uncommon to see the same job running 10x or 100x faster with the same clusters, the same data, just a different approach.

Study on AI and the Future of Sales

Whether it’s redefining the world of marketing, finance or customer support, it is no secret that artificial intelligence (AI) is changing the way we work. Sales, as both a function and a profession, is no exception to the sea change. Our friends over at Cien produced a global study: The Future of Sales that reveals how attitudes, perception and behavior of high tech sales professionals is not what is often touted in the media.

An Introduction to NoSQL Databases

In the video presentation below, Bart Baesens, Professor of Big Data & Analytics, discusses a series of non-relational database management systems which focus specifically on being highly scalable in a distributed environment: NoSQL databases. The presentation is an extract from an upcoming book Principles of Database Management.

“Intelligent Storage” Market Survey Shows Growing Problem Moving Large Data Sets for a Variety of Applications

G2M Research, an analyst firm covering the Non-Volatile Memory Express® (NVMe) marketplace, released the results of its recent survey on the need for “Intelligence storage” for applications with large data sets. The survey, sponsored by NGD Systems, was conducted across 112 respondents from organizations involved in Big Data, artificial intelligence/machine learning, and Internet of Things (IoT) applications.

How Computers Learn

This Vienna Gödel Lecture provides a fascinating talk by Peter Norvig, Research Director at Google Inc. in the field of intelligent computers. Norvig talks about his long experience in AI and Machine Learning. The talk explains how computers learn from examples and what are the promises and limitations of these techniques.

Interview: Vivienne Sze, Associate Professor of Electrical Engineering and Computer Science at MIT

I recently caught up with Vivienne Sze, Associate Professor of Electrical Engineering and Computer Science at MIT, to discuss the launch a new professional education course titled, “Designing Efficient Deep Learning Systems.” The two-day class will run March 28-29, 2018 at the Samsung Campus in Mountain View, CA and will explore all the latest breakthroughs related to efficient algorithms and hardware that optimize power, memory and data processing resources in deep learning systems.

Operationalizing Data Science

In the video presentation below, Joel Horwitz, Vice President, Partnerships, Digital Business Group for IBM Analytics, discusses what it means to “operationalize data science” – basically what it means to harden the ops behind running data science platforms.