Richard Creamer's Personal Website Links Resumes
Welcome to my personal website summarizing my interests, projects, and prior work examples.
Tagline: interested in things that are interesting :-)
I have worn software engineer/architect, entrepreneur, product manager, and principal investigator hats spanning over 25 years in multiple, diverse fields, including many key startup roles. Currently, I am interested in doing technology projects with the potential to have a major impact on children and the world which utilize web-scale health analytics, new education/learning technologies, and applied computational argumentation/collaboration. Finally, I really enjoy and excel at entering and innovating in new domains. I currently live in Northern California.
- Web-scale health analytics
- Redefine education and learning technologies
- Pervasive use of computational critical thinking/argumentation
- Novel application of [subject, predicate, object, uid] 4-tuples for expressing knowledge, data, graph metadata, vocabularies, UX, and more
- Stereo imaging and graphics, augmented reality
- Machine Learning, Computer Science, AI, Optimization, Mathematics
- Next-generation social networking platform architecture
- Hobbies: photography, music/guitar
Work & Education
- Innovest Systems, Software Engineer, 2014 - present
- Cool Apps Software, Software Engineer, 2012 - present
- University of California, Davis, B.S. Applied Physics
Education, Online (Coursera.org)
- University of Washington
- Georgia Tech
- Johns Hopkins University
I rarely update this website anymore, but below are mostly older, historical updates...
- Python kNN classification exercise [Oct-2016]
- Currently (Fall-2016) studying Python's Machine Learning libraries:
- Numpy + SciKit-Learn
- Here is a plot I coded using Matplotlib and a data set from one of the Python ML books I'm studying
- Mean Absolute Deviation in Python/Numpy - my StackOverflow answer
- This looks to be a good introduction to Deep Learning (URL)
- By invitation and for the 2nd time, I will again be a Community TA for the Stanford online Machine Learning course beginning Sept. 22, 2014 (Coursera).
- Kaggle.com Higgs Boson Challenge
- The purpose of this challenge was to identify a particular Higgs Boson decay event from background noise data.
- Below is a histogram of the predicted Real output numbers from an early Random Forest classifier. The best threshold on these Real outputs was found by applying the quantile() R function on the Train set labels.
- A few more details are here.
- Project Euler Solutions (coding examples):
- I just added a new page w/solutions to a few selected Project Euler problems. PLEASE do not use this code on ProjectEuler.net !
- Weight Lifting Exercises Dataset (Summary Page)
- I recently built a Random Forest classifier in R which classifies a human's exercise activity from 52 accelerometer and tilt/gryo sensor measurements. The training set had about 19,000 labeled samples.
- CodeEval Challenge: A quick C hack got me a 99.841% ranking on a CodeEval.com programming challenge:-) PLEASE do not use my code on CodeEval.com !
- Recent online ML/Data Science courses:
- Completed 3 online courses from the Johns Hopkins Data Science specialization series on Data Science:
- Certificates of completion and course topic summaries can be viewed here
- I just learned about and joined CodeEval.com, looking forward to finding time to solve some of the interesting challenges on this site!
- I just progressed to Level 2 on ProjectEuler.net (top 7.26%) by completing 50+ problems. Update: I added a new page w/ selected solutions/code. Screenshot showing advancement to Level 2:
Slide decks (Click left link to go to Slide Decks page)
- Concluded role as online Stanford Machine Learning course Community TA! (part-time) - last day of course: May 26, 2014
|Additional online courses I've completed
Links of Interest
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Disclaimer: Any comments, ideas, IP, or opinions I make 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.
Copyright © Richard Creamer 2008 - 2016 - All Rights Reserved
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