The Google Developers Show: Episode TL;DR 138
Fast Pair Update → http://bit.ly/2zHwxDG
SDK Developers: stay up to date → http://bit.ly/2rqHl4F
New GCP regions in Hong Kong and Jakarta → http://bit.ly/2rnjvH1
Google Data Studio with Crashlytics data → http://bit.ly/2E6Jslt
Chrome 72 DevTools → http://bit.ly/2QAQsxY
The Google Developer Show brings you the latest developer news from across Google. Your host for this week is Developer Advocate Dan Galpin (https://twitter.com/dagalpin). Expect a new Dev Show episode every week, and let us know what you think of the latest announcements in the comments below!
A Day In The Life Of A Computer Software Engineer – Vlog
hey YouTube! I work as a software engineer and here’s my typical day.
Thanks for joining!
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Music by Favorite August: https://artlist.io/song/4557/belief?tempo=medium&durmin=240&durmax=336
Channel: Life of Luba
Published: 2018-03-06 07:05:37
Quantum computing explained with a deck of cards | Dario Gil, IBM Research
We are moving rapidly toward quantum computing. How does the technology work and what does it mean for our future? Scientist Dario Gil, VP of Science and Solutions at IBM, provides clarity on this complex topic. David Morczinek gives the introduction.
The MIT Venture Capital + Innovation Conference is held annually in February at the MIT Sloan School of Management. Thank you to our lead sponsor IBM Research, as well as Solvay, Wilmer Hale, Finnegan, The MIT Industrial Liaison Program, the MIT Startup Exchange, and Startup Hub Boston. Visit http://www.mitvcconference.com/.
Dr. Gil is a leading technologist and senior executive at IBM. As Vice President of Science and Solutions of IBM Research, Dr. Gil directs a global organization of some 1,500 researchers across 11 laboratories. He has direct responsibility for IBM’s science agenda, with a broad portfolio of activities spanning the physical sciences, the mathematical sciences, healthcare and the life sciences. Dr. Gil is also responsible for IBM’s cognitive solutions research agenda, which aims to create scientific and technological breakthroughs to differentiate IBM’s solutions businesses and serves as an incubator for future cognitive industry solutions for IBM and its clients.
Dr. Gil is a passionate advocate of collaborative research business models and is the creator and Founding Director of two research consortia: the IBM Research Frontiers Institute and the Smarter Energy Research Institute. An expert in the field of nanofabrication, he led the team that built the world’s first microprocessor with immersion lithography in 2004.
Dr. Gil is a frequent speaker at business events, conferences (including TED), universities, research institutions and foundations. His research results have appeared in over 20 international journals and conferences, and he is the author of numerous patents. Dr. Gil is a member of the Future Trends Forum, the Industrial Advisory Group of the Institute of Photonic Sciences and an elected member of the IBM Academy of Technology. He received his Ph.D. in electrical engineering and computer science from the Massachusetts Institute of Technology.
Channel: MIT Venture Capital & Innovation
Published: 2017-06-21 18:07:49
We built the Home of the Future with Grant Imahara
The Verge and Curbed have teamed up to build the home of the future. Join host Grant Imahara as he examines the renewed trend of prefabricated modular home construction.
Like The Verge on Facebook: https://goo.gl/2P1aGc
Subscribe to Verge Science on YouTube, a new home base for our explorations into the future of science: http://bit.ly/2FqJZMl
Channel: The Verge
Published: 2018-08-03 21:48:50
What Makes a Good Feature? – Machine Learning Recipes #3
Good features are informative, independent, and simple. In this episode, we’ll introduce these concepts by using a histogram to visualize a feature from a toy dataset. Updates: many thanks for the supportive feedback! I’d love to release these episodes faster, but I’m writing them as we go. That way, I can see what works and (more importantly) where I can improve.
We’ve covered a lot of ground already, so next episode I’ll review and reinforce concepts, introduce clearer syntax, spend more time on testing, and continue building intuition for supervised learning.
I also realize some folks had dependency bugs with Graphviz (my fault!). Moving forward, I won’t use any libraries not already installed by Anaconda or Tensorflow.
Last: my code in this cast is similar to these great examples. You can use them to produce a more polished chart, if you like:
Follow https://twitter.com/random_forests for updates on new episodes!
Channel: Google Developers
Published: 2016-04-27 15:56:13