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Richard Creamer
Works at Innovest Systems
Attended UC Davis, BS Physics
Lives in Northern California
27,396 followers|7,947,068 views
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Richard Creamer

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ML symposium Oct 22, 2015 SF Bay area
#machinelearning  
 
BayLearn will be held October 22nd, 2015.  This is the premier Machine Learning symposium in the San Francisco Bay Area, including keynotes by Jeff Dean​, Yann LeCun​, and Trevor Darrell​. Well worth attending if you live in the area, so save the date!  We also just opened up the website for abstract submissions. I hope to see many of you there in October, and am also happy that Baidu Research is the event's main sponsor. Go to: http://www.baylearn.org/overview
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Leonor Maertz's profile photoPaul Brown's profile photoRichard Creamer's profile photo
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Thank you, +Leonor Maertz​ and +Paul Brown​!
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Richard Creamer

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New Data Science Central data science course

I saw this go by and decided to reshare it.  Disclaimer:  I have not looked at the course in depth.  That said, from the page below, it looks like some important foundational topics are not included, but nevertheless...
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Great share
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I got a similar idea a year or so ago, glad to see someone is looking into this (I hope)...
#climatechange   #globalwarming  
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Muy bueno.
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Stoneman Bridge over Merced River
25 sec. exposure, HD 1920 x 1080 px

Here is a rather subdued image taken about a month ago.  I smoothed the water with a 25-second exposure by using a 1,000x neutral density filter.

#yosemite   #yosemitevalley   #mercedriver  
#landscapephotography  +Landscape Photography +Margaret Tompkins +Kevin Rowe +Toshi Nakamura +Bill Wood +Tony Phillips +Jeff Beddow +Krzysztof Hanusiak +Dennis Hoffbuhr +Dave Gaylord +Doug Hagadorn +Eric Drumm +RJ Wilner 
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Thank you, +tammy o'donnell!
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Richard Creamer

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I needed a function to split a list into multiple smaller lists in order to distribute data to multiple worker threads.  This is part of a small image processing side project I'm writing at home in my spare time.
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Thank you, +selvaraj selvam!
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This looks to be an interesting tutorial (I haven't read it yet, though).

http://deeplearning.stanford.edu/tutorial/

#machinelearning   #deeplearning  
Description: This tutorial will teach you the main ideas of Unsupervised Feature Learning and Deep Learning. By working through it, you will also get to implement several feature learning/deep learning algorithms, get to see them work for yourself, and learn how to apply/adapt these ideas to new ...
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Android dev tips right from the horses' mouths, so to speak ;-) #android
Update: Here is a link to the entire Android dev series:
https://plus.google.com/+ChetHaase/posts/a8ssyRqJy7a
 
Introducing: Developing for Android

Many of the folks on the Android platform team got together and collected some of our thoughts into a surprisingly long article that attempts to answer the leading question: "What are some of the important rules to keep in mind when developing Android applications?"

We've broken this article up into several more manageable sections to suit the short-attention-span public and will be publishing them in the next few days on Medium.com, in the new Google Developers collection. Today, we'll start with the quick Intro and my favorite chapter, aka Chapter I, which sets the stage by explaining why it's important to understand the rules.

I'd like to thank everyone that contributed to the doc, but there are just too darned many to remember, so I'll stick with a few of the folks that kicked in significant chunks (but thanks to everyone else, too):
+Adam Powell 
+Dianne Hackborn 
+Jeff Brown 
+Jeff Sharkey 
+Shai Barack 
+Brian Carlstrom 
+Chris Craik 
+George Mount 
+yiğit boyar 
+Christopher Tate 
And everyone else!

Intro:
https://medium.com/google-developers/developing-for-android-introduction-5345b451567c

Chapter I: Understanding the Mobile Context
https://medium.com/google-developers/developing-for-android-i-understanding-the-mobile-context-fd2351b131f8?source=your-stories
This article (or, rather, series of articles, since a sense of decency and understanding of short-attention-span readers…
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Education
  • UC Davis, BS Physics
  • Stanford (online)
    Machine Learning
  • University of Washington (online)
    Intro to Data Science
  • Georgia Institute of Technology (online)
    Computational Photography
  • Johns Hopkins University (online)
    Machine Learning/Data Science
Basic Information
Gender
Male
Looking for
Networking
Relationship
Married
Other names
Rick
Story
Tagline
I want to do things that matter
Introduction
  • I can do *
  • Coder, Technical Product Manager, more...
  • Image Processing, UX, Machine Learning, Knowledge Graphs
  • Photography, Music
Note: I follow around 5,000 people = maximum, so am maxed out :-(

Interests
  • C.S., Education, Health, Social Network Platforms
  • Machine Learning, KG/KB, Semantic Web, CUDA
Hobbies
  • Landscape photography, stereo photography, guitar
CV     LinkedIn Profile      Personal Website     Github

Disclaimer: Any comments, ideas, Intellectual Property, or opinions I place on the Web are entirely my own and are completely distinct from, do not reflect upon, or represent in any way, my employers - past, present, and future.
Work
Occupation
Coder, Technical Product Manager, UX
Skills
I can code just about anything
Employment
  • Innovest Systems
    Software Engineer, 2014 - present
  • Cool Apps Software
    Software Engineer, 2012 - present
Places
Map of the places this user has livedMap of the places this user has livedMap of the places this user has lived
Currently
Northern California
Previously
San Jose