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Q# 101: Getting to know the basics of Microsoft’s new quantum computing language

A few days back we posted about the preview of Microsoft‘s development toolkit with a new quantum programming language, simulator,…

NIPS 2017 Special: How machine learning for genomics is bridging the gap between research and clinical trial success by Brendan Frey

Brendan Frey is the founder and CEO of Deep Genomics. He is the professor of engineering and medicine at the…

NIPS 2017 Special: 6 Key Challenges in Deep Learning for Robotics by Pieter Abbeel

Pieter Abbeel is a professor at UC Berkeley and a former Research Scientist at OpenAI. His current research focuses on…

3 great ways to leverage Structures for Machine Learning problems by Lise Getoor at NIPS 2017

Lise Getoor is a professor in the Computer Science Department, at the University of California, Santa Cruz. She has a…

20 lessons on bias in machine learning systems by Kate Crawford at NIPS 2017

Kate Crawford is a Principal Researcher at Microsoft Research and a Distinguished Research Professor at New York University. She has…

Top Research papers showcased at NIPS 2017 – Part 2

Continuing from where we left our previous post, we are back with a quick roundup of top research papers on…

Top Research papers showcased at NIPS 2017 – Part 1

The ongoing 31st annual Conference on Neural Information Processing Systems (NIPS 2017) in Long Beach, California is scheduled from December…

10 Algorithms every Machine Learning Engineer should know

Machine Learning (ML) is an extremely powerful tool to make predictions based on huge amounts of data. According to a…

Highest Paying Data Science Jobs in 2017

It is no secret that this is the age of data. More data has been created in the last 2…

Expert Insights: How sports analytics is empowering better decision-making

Analytics is slowly changing the face of the sports industry as we know it. Data-driven insights are being used to…