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Book Review: Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning

We’re seeing a rising number of new books on the mathematics of data science, machine learning, AI and deep learning, which I view as a very positive trend because of the importance for data scientists to understand the theoretical foundations for these technologies. In the coming months, I plan to review a number of these […]

causaLens Launches Causal AI Platform

causaLens, a deep-tech company predicting and optimising the global economy, has released a new causal Artificial Intelligence (causal AI) enterprise platform. Businesses no longer have to rely on curve-fitting machine learning platforms unable to handle the complexity of today’s world. They are invited to join the real AI revolution with a platform that understands cause and effect.

“Above the Trend Line” – Your Industry Rumor Central for 9/19/2020

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.

KDD 2020 Celebrates Recipients of the SIGKDD Best Paper Awards

KDD 2020, the premier interdisciplinary conference in data science (which took place virtually Aug. 23-27, 2020), announced the recipients of the SIGKDD Best Paper Awards, recognizing papers presented at the annual SIGKDD conference that advanced the fundamental understanding of the field of knowledge discovery in data and data mining. Winners were selected from more than 2,000 papers initially submitted for consideration to be presented at the conference.

insideBIGDATA Latest News – 9/12/2020

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.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – August 2020

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.

“Above the Trend Line” – Your Industry Rumor Central for 9/4/2020

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.

TOP 10 insideBIGDATA Articles for August 2020

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.

Research Highlights: Attention Condensers

A group of AI researchers from DarwinAI and out of the University of Waterloo, announced an important theoretical development in deep learning around “attention condensers.” The paper describing this important advancement is: “TinySpeech: Attention Condensers for Deep Speech Recognition Neural Networks on Edge Devices,” by Alexander Wong, et al. Wong is DarwinAI’s CTO.

Book Review: Deep Reinforcement Learning Hands-On

RL is a hugely popular area of deep learning, and many data scientists are exploring this AI technology to broaden their skillet to include a number of important problem domains like chatbots, robotics, discrete optimization, web automation and much more. As a result of this wide-spread interest in RL, there are many available educational resources specifically tailored to this class of deep learning – boot camps, training certificates, educational specializations, etc. But if you’re a data scientist who has been programming in Python for a while, and has some experience with other forms of deep learning using a framework like TensorFlow, then maybe this new book, “Deep Reinforcement Learning Hands-On,” by Maxim Lapan, might be a great way to kick-start yourself into becoming productive with RL.