Kepler.gl is a tool designed for geospatial data analysis. This guide will help you get started creating visualizations in
CPSC 540: Machine learning
Great resources for learning machine learning from a UBC professor
Decision Intelligence with Cassie Kozyrkov: GCPPodcast 128 – YouTube
Chief Decision Scientist, Cassie Kozyrkov joins Mark and Melanie this week to explains what is data science, analytics, machine learning and statistical inference is, in relation to decision intelligence.
Prediction intervals for Random Forests | Diving into data
. A prediction of 0.5 could mean that we have learned very little about a given instance, due to observing no or only a few data points about it. Or it could be that we have a lot of data, and the response is fundamentally uncertain, like flipping a coin.
Google to invest $550 million in China e-commerce giant JD.com as it battles rivals | The Japan Times
Google will invest $550 million in Chinese e-commerce powerhouse JD.com, part of the U.S. internet giant’s efforts to expand its presence in fast-growing Asian markets and battle rivals including Amazon.com.
Communico – Fostering “Googleyness” in your Organization: Five Key Factors for Success
Aside from their renowned perks like sushi, salads and massages, the organization makes sure its associates feel heard and challenged.
Mental Models: The Best Way to Make Intelligent Decisions (113 Models Explained)
How do you think the most rational people in the world operate their minds? How do they make better decisions?
The Most Powerful Lesson I’ve Ever Learned In Business
Years from now, when you look back on your career, and your life, success or failure will matter a lot less than whether you got there by keeping or compromising your principles.
re:Work – The five keys to a successful Google team
hatever you call it, you’re part of one at Google and probably wherever you work: a team. So if we know what makes managers great, why don’t we know what makes a team great?
How will the GDPR impact machine learning? – O’Reilly Media
This article aims to demystify this intersection between ML and the GDPR, focusing on the three biggest questions I’ve received at Immuta about maintaining GDPR-compliant data science and R&D programs. Granted, with an enforcement data of May 25, the GDPR has yet to come into full effect, and a good deal of what we do know about how it will be enforced is either vague or evolving (or both!). But key questions and key challenges have already started to emerge.