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In the News
AI for cybersecurity is a hot new thing—and a dangerous gamble
Machine learning and artificial intelligence can help guard against cyberattacks, but hackers can foil security algorithms by targeting the data they train on and the warning flags they look for.
Face Off: Law enforcement use of face recognition technology
"Face recognition is poised to become one of the most pervasive surveillance technologies, and law enforcement’s use of it is increasing rapidly. Today, law enforcement officers can use mobile devices to capture face recognition-ready photographs of people they stop on the street; surveillance cameras boast real-time face scanning and identification capabilities; and federal, state, and local law enforcement agencies have access to hundreds of millions of images of faces of law-abiding Americans. On the horizon, law enforcement would like to use face recognition with body-worn cameras, to identify people in the dark, to match a person to a police sketch, or even to construct an image of a person’s face from a small sample of their DNA."
Data-mining medieval text reveals medically bioactive ingredients
Medieval apothecaries used recipes with significant antibacterial properties, researchers say.
Workplace
Hiring for autonomy in Data Science teams
Interview with Eric Colson, Chief Algorithms Officer for Stitch Fix, an online subcription personal shopping service, on Stitch Fix's engineering culture works, including what they value, what they look for in new hires, and how they’ve architected their platform to enable astounding success.
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Learning
The total beginner's guide to Game AI
This article will introduce you to a range of introductory concepts used in artificial intelligence for games (or ‘Game AI’ for short) so that you can understand what tools are available for approaching your AI problems, how they work together, and how you might start to implement them in the language or engine of your choice.
Facebook Field Guide to Machine Learning video series
Six-part video series developed by the Facebook ads machine learning team. The series shares best real-world practices and provides practical tips about how to apply machine-learning capabilities to real-world problems.
Running Agile Machine Learning Experiments
Learning Math for Machine Learning
Software tools & code
9 things you should know about TensorFlow
Classification datasets results
Summary of the current state of the art in image classification.
About
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