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5/14
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Keras (Python Deep Learning framework)
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https://keras.io/
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5/14
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Keras in R
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https://keras.rstudio.com/
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5/6
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Computational Journalism
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https://engineering.stanford.edu/magazine/article/what-future-computational-journalism
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5/4
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Shiny: interactive data apps with R
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http://shiny.rstudio.com/
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5/4
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D3.js: interactive data visualization for JavaScript
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https://d3js.org/
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4/29
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A commentary on the Santa Clara study I alluded to (from Andrew Gelman, his blog is quite the resource, highly recommended)
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https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/
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4/27
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a16z: Another podcast I like (for those with an entrepenurial bent)
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https://a16z.com/2020/04/26/journal-club-machine-learning-antibiotics-coronavirus-protein-structures/
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4/22
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From the StitchFix Data Science Blog
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https://multithreaded.stitchfix.com/blog/2019/03/11/FullStackDS-Generalists/
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4/15
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More on gradient descent
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https://towardsdatascience.com/understanding-the-mathematics-behind-gradient-descent-dde5dc9be06e
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4/8
|
Hacking pdfs for mobility data
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https://www.nxn.se/valent/2020/4/7/converting-images-of-line-graphs-to-data
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4/6
|
Kaggle COVID-19 Open Research Dataset Challenge
|
https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge
|
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4/1
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Visual explanation of stats and probability
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http://students.brown.edu/seeing-theory/
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3/11
|
COVID-19 Data
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https://github.com/CSSEGISandData/COVID-19
|
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3/9
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Uber Engineering Blogpost: platform in 2019
|
https://eng.uber.com/uber-data-platform-2019/
|
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3/9
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Uber Engineering Blogpost on their Data Science Workbench
|
https://eng.uber.com/dsw/
|
|
3/4
|
NASA's Helio Hackweek
|
https://heliohackweek.github.io/
|
|
2/24
|
Data Science is becoming Software Engineering
|
https://towardsdatascience.com/data-science-is-becoming-software-engineering-53e31314939a
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|
2/19
|
One take on Data Science Survey
|
https://www.theverge.com/2017/11/1/16589246/machine-learning-data-science-dirty-data-kaggle-survey-2017
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|
2/17
|
Example wrangling with R and Python
|
https://www.superdatascience.com/wrangling-data-r-python/
|
|
2/12
|
The Julia programming language
|
https://julialang.org/
|
|
2/10
|
Best practices for computational science
|
https://openresearchsoftware.metajnl.com/articles/10.5334/jors.ay/
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2/10
|
Good enough practices in scientific computing
|
http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005510
|
|
2/7
|
RStudio conference just finished last week
|
https://resources.rstudio.com/rstudio-conf-2019
|
|
1/29
|
Data Skeptic: Podcast and more
|
https://dataskeptic.com/
|
|
1/27
|
Enterprise Data Analysis and Visualization: An Interview Study. Sean Kandel, Andreas Paepcke, Joseph Hellerstein, Jeffrey Heer
|
https://idl.cs.washington.edu/papers/enterprise-analysis-interviews/
|
|
1/27
|
David Donoho (Stanford Prof. of Statistics): 50 years of Data Science
|
https://www.tandfonline.com/doi/full/10.1080/10618600.2017.1384734
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