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Why 3D is the Key to Unlocking Vital Video Surveillance Data

In this contributed article, Srinath Kalluri, CEO of Oyla, suggests that by blending AI, 3D and video analytics, businesses will be able to bring better information to big data and enable smarter and safer ways of working.

Video Highlights: Generalized Additive Models – Allowing for some wiggle room in your models

In this video presentation, we’ll unpack GAMs as an extension of generalized linear models, learn about the role of splines in these models, and explore the many choices available to define and fit these models. We’ll be using data on traffic stops to investigate racially-biased policing in South Carolina as a motivating example, and we’ll get a chance to try out the related R code so that you have the basic tools needed to try out GAMs in your own research context.

Video Highlights: Business Analyst or Data Scientist? What Field to Choose If you Want to Launch a Startup in Future

This Data Science Salon (DSS) video is presented by Julia Khan, Vice President of Analytics at SEMrush. This presentation will be most useful for young data professionals, who are trying to choose their own path within the wide range of specializations inside the data science field.

JADBio Provides AutoML for BioMed Data

JADBio is an AI startup company working with BioMed data. This remarkable team, headed by Prof. Ioannis Tsamardinos, has created an automated machine learning (AutoML) platform designed for life scientists. No Coding. No Statistics. No Math. No Problem … just add data.

Cambridge Quantum Computing Pioneers Quantum Machine Learning Methods for Reasoning

Scientists at Cambridge Quantum Computing (CQC) have developed methods and demonstrated that quantum machines can learn to infer hidden information from very general probabilistic reasoning models. These methods could improve a broad range of applications, where reasoning in complex systems and quantifying uncertainty are crucial. Examples include medical diagnosis, fault-detection in mission-critical machines, or financial forecasting for investment management.

Video Highlights: Unleashing DataOps Keynote

In this keynote presentation from the DataOps Unleashed virtual conference, innovator Kunal Agarwal, CEO of Unravel Data, describes how companies large and small are using DataOps to make their technology stacks hum, get more done at a lower cost, and improve both customer experience and the bottom line.

The Big Data Dilemma

The Big Data Dilemma made a huge splash in the last Fundata Film Festival – the best-kept secrets of both the film and data industries – and grabbed the Official Selection designation of 2021. Shattering the ‘data-driven’ hype and revealing the coin-flipping truth, The Big Data Dilemma brings together global data anti-vangelists to tell it as it is, or at least as they believe it is.

Video Highlights: AI’s Role in Fight Against COVID-19

Legal and compliance technology company, Relativity premiered its latest installment of its On the Merits documentary series, which aims to showcase how people use data for the greater good. This year’s documentary explores how AI was leveraged in the race for answers around COVID-19.

Video Highlights: Deep Learning for Probabilistic Time Series Forecasting

In this Data Science Salon talk, Kashif Rasul, Principal Research Scientist at Zalando, presents some modern probabilistic time series forecasting methods using deep learning. The Data Science Salon is a unique vertical focused conference which grew into the most diverse community of senior data science, machine learning and other technical specialists in the space.

Video Highlights: Why Do ML Models Fail?

Our current machine learning (ML) models achieve impressive performance on many benchmark tasks. Yet, these models remain remarkably brittle, susceptible to manipulation and, more broadly, often behave in ways that are unpredictable to users. Why is this the case? In this talk by Aleksander Madry, Professor of Computer Science, Massachusetts Institute of Technology, we identify human-ML misalignment as a chief cause of this behavior.