August 2015 Items of Interest

August Meetups:

757 Python User’s Group: Tuesday, 04 August.

7:00 pm at the Hampton Public Library, 4207 Victoria Blvd., Hampton.

Brian Magill, senior programmer at Science Systems and Applications, will discuss Python Iterators and Generators, with an emphasis on Generators.

Tidewater Analytics: Tuesday, 11 August

7:00 pm at 757 Creative Space, 259 Granby St. Suite 250, downtown Norfolk.

Steve Mortimer, Data Scientists at Dominion Enterprises, will lead a hands-on workshop on Git and GitHub.

757 R User’s Group:

There will be no R User Group meeting in August. The next meeting will be on Tuesday, 15 September

Other Meetup News:

Tidewater Big Data Enthusiasts:

7:00 pm, Tuesday, 22 September at 757 Creative Space, 259 Granby St. Suite 250, Norfolk

Dr. Chuck Cartledge, computer scientist and adjunct professor at Tidewater Community College, is kicking off the area’s newest meetup on Big Data.

Team Tidewater Kaggle group forming:

An open group for competing in Kaggle competitions will be forming in September. This will be open to anyone who wants to learn, improve, and simply participate at any level, and there will be room for a very diverse range of skills and interests.

There will be more information about this at both the August and September Tidewater Analytics Meetups. But if you think you might be interested, this would be a good blog post to take a peek at: Kaggle Competition Tips and Summaries, as well as this Kaggle R Tutorial on Machine Learning.

MOOCs and other educational venues:

Coursera:

Reasoning, Data Analysis, and Writing

Nationally-known and highly-regarded data scientist Hilary Mason has said that the single biggest skill lacking in data science is the ability to tall a narrative about the data. This Coursera specialization, taught by Duke University, seems like a very good candidate for helping address that shortfall.

Big Data University

Introduction to R

 I cannot vouch for the quality of the instruction, but they seem to hit on all the right topics for a beginner course.

Data Camp:

Intermediate R

As with the Introduction to R course, above, I cannot vouch for this. But again, the topics seem to be spot on.

Books and such:

Exploratory Data Analysis (EDA) with R

Dr. Roger Peng, who teaches the R portion of Coursera’s Johns Hopkins Data Science specialization, put out this excellent book on Exploratory Data Analysis with R.

From the web site description: This book teaches you to use R to effectively visualize and explore complex datasets. Exploratory data analysis is a key part of the data science process because it allows you to sharpen your question and refine your modeling strategies. This book is based on the industry-leading Johns Hopkins Data Science Specialization, the most widely subscribed data science training program ever created.

Miscellaneous:

Python 3.5 released

Here is a summary of new and improved features in the recently released Python 3.5.

Johns Hopkins Data Science Hack-a-Thon

It’s a bit of a haul, but the same Johns Hopkins folks who teach the Coursera Data Science track are sponsoring a Data Science Hack-a-Thon in Baltimore on 21 – 23 September 2015.

Data Science Machine Learning Cheat Sheets:

KDNuggest has an excellent post that lists over 50 data science and machine learning cheat sheets.

Curated Data Science Information on GitHub:

Analytics Vidhya has a pretty cool post on the various Data Science resources available on GitHub.

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