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Issue #29

Dec 15, 2019

Dear friends,

Thank you for joining us for this weeks issue of the Sunday Briefing. This week we focus on the big picture with Stanford's AI Index Report and Joshua Bengio's push for causality in AI. We get in the weeds with a Microsoft blog post on how to search for efficient neural architectures, a review of ML in the physical Sciences, an introduction to Recurrent Neural Networks an overview of logistic regression models in aggregated data.

Finally, in the video of the week Patrick Winston give us a thorough overview of Support Vector Machines.

If you think one of your friends or colleagues would enjoy this newsletter, just go ahead and forward this email to them and help us grow!

Semper discentes,

The D4S team

Top Links:

Tutorials and blog posts that came across our desk this week.
  1. Artificial Intelligence Index Report 2019 [hai.stanford.edu]
  2. Quantum computing gains a first foothold in investment banking [medium.com/@IBMResearch]
  3. An AI Pioneer Wants His Algorithms to Understand the 'Why' [wired.com]
  4. When did societies become modern? ‘Big history’ dashes popular idea of Axial Age [nature.com]
  5. Project Petridish: Efficient forward neural architecture search [microsoft.com]
  6. The Huge, Unseen Operation Behind the Accuracy of Google Maps [wired.com]
  7. Building a search engine from scratch [0x65.dev]

Fresh off the press:

Some of the most interesting academic papers published recently.

Video of the week:

Interesting discussions, ideas or tutorials that came across our desk.


Support Vector Machines

https://www.youtube.com/watch?v=_PwhiWxHK8o

Upcoming Events:

Opportunities to learn from us
  1. Jan 17, 2019 - Time Series for Everyone [Register
  2. Jan 27, 2019Applied Probability Theory for Everyone [Register🆕
  3. Mar 15-16, 2019Time series modeling: ML and deep learning approaches - Strata/AI [Register
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