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We use react to control the view and D3.js, chart.js to draw visualization.

Great site, what were the visualizations built with?

paper draft here: https://github.com/dfm/celerite/blob/master-pdf/paper/ms.pdf

Mike, it depends. You can check the comparative examples NLP and buttons in the article!

How about Natural Language Processing instead?
1 point by acadian04 3 days ago | link | parent | on: R Tutorial for Beginners

This is a new concise R tutorial on the statmethods site.

Sixpack is a AB test framework rather a visualization solution. It may not be suitable when you want to monitor 10x metrics across multiple a/b tests

I think https://github.com/seatgeek/sixpack does that.

Thanks for your answer ! Any specific dashboard example that I can get started with on Grafana for A/B visualization? I see that most of the Grafana examples are suited for monitoring engineering metrics.

No probs)

Thanks. Great that it's using Stan.

We use a combination of a Python backend (https://github.com/zalando/expan) and Grafana/KairosDB.

This is news to me. Thanks for the info.

As long as I know, Statsbot works not only with Slack, but with Microsoft Teams as well. And it's preparing new integrations

I can see this potentially alleviating the smaller ad-hoc burden off of analytics, however, most likely only for companies who are currently using Slack.

In addition to their AI activity, I wonder how Slack is planning to evolve their suite of services.


bump

Big Data Day LA is on Aug 5, 2017 at the University of Southern California in Los Angeles. Attendance is free, and we are currently open for registration and are accepting submissions for speakers, sponsors, volunteers.

This is part 1 of a series of posts revising the visualizations from O'Reilly Media's 2016 Data Science Salary Survey (by authors John King & Roger Magoulas).

Thanks @argotechnica, we have updated the link.

Thanks @larrydag, that's an interesting list!

The Hopcroft and Kannan book has been updated since the 2014 edition linked to from that article, to this 2016 version, with an additional author (Blum): https://www.cs.cornell.edu/jeh/book2016June9.pdf

This is an essential read for those that use Python.

Here is some essential reads for those that use R

Regression Modeling Strategies - F. Harrell http://www.springer.com/gb/book/9781441929181

Elements of Statistical Learning - Hastie et al https://statweb.stanford.edu/~tibs/ElemStatLearn/

Introduction to Statistical Learning - James et all http://www.springer.com/us/book/9781461471370

The Art of R Programming - N. Matloff https://www.nostarch.com/artofr.htm


It seems like a nice start, i think the stuff most lacking everywhere is errors,tools and redshift's limitation

I would add on the following tools: - Redshift monitoring https://github.com/awslabs/amazon-redshift-monitoring - Redshift admin queies and views https://github.com/awslabs/amazon-redshift-utils/tree/master... and https://github.com/awslabs/amazon-redshift-utils/tree/master... - spark-redshift https://github.com/databricks/spark-redshift - snowplow https://github.com/snowplow/snowplow

I would also add about limitation and how to overcome it: - copy of json vs csv (Non Strict/Strict schema) - limitation of udf (no input possible) - listagg on more than varchar(max) using ... - some redshift sql tricks like (equivalent to generate_series) https://github.com/eyaltrabelsi/my-notebooks/blob/master/tot... - Emphasize lack of recursive functions& triggers and more and how one would fix it using code other tools

ERROR handling: - SSL - load errors

and some more advanced stuff like: - dynamic schemas since data+quries alive how would one generate schemas - wlm and the new features - auto scaling the cluster when/how few slices with big storage vs many slices (Network IO vs parallelize)


Part 2: https://medium.com/athelas/baidu-deep-voice-explained-part-2...
1 point by ata_aman 15 days ago | link | parent | on: Google is acquiring Kaggle

gathering data from that is way more valuable than stopping their competitors imho
1 point by icc97 15 days ago | link | parent | on: Google is acquiring Kaggle

If they stopped competitors using it then they'd effectively kill Kaggle.
2 points by data_dude 16 days ago | link | parent | on: Google is acquiring Kaggle

Exactly my thoughts too. I remember Netflix had a huge one a while ago. If it directly conflicts with Google Youtube's interests, arguably it could mean Google will be able to dictate competitions and have a 500K army of data scientists at their disposal.

Have been following Jeff Hawkins work on Hierarchical Temporal Memory ever since I read his book "On Intelligence", so I found this old news interesting :)

Are you applying any theory from the Hierarchical Temporal Memory work by Jeff Hawkins? (https://github.com/numenta/nupic/wiki/Hierarchical-Temporal-...)

It seemed to be great at forecasting periodic trends too, so that's why I wonder ...


Bit of an unfortunate name clash with a very popular bioinformatics tool: http://bowtie-bio.sourceforge.net/index.shtml

Not that this does not happen all the time anyway, but just a heads up.

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