For those of you who wish to begin learning Python for Data Science, here is a list of various resources that will get you up and running. Included are things like online tutorials and short interactive course, MOOCs, newsletters, books, useful tools and more.
Python Tips decided to put this together so that you can…
Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week.
Added by Vincent Granville on July 30, 2016 at 9:00am — No Comments
Even today there seems to be considerable debate over the exact meaning of "stress." During my graduate studies, I pointed out that there are similar themes in the literature pertaining to stress; that perhaps researchers have been overemphasizing the differences. Among the most persistent themes is the distinction between stress and stressors. Hans Selye asserted in 1936 is that stress is an internal response against any form of noxious stimulant. He described the environmental factors…Continue
Added by Don Philip Faithful on July 30, 2016 at 7:30am — No Comments
The Brussels data science community is pleased to announce the first data science bootcamp organized in Europe aimed at young potentials.Continue
Added by Philippe Van Impe on July 30, 2016 at 4:39am — No Comments
This notebook was written by Dr. Randal S. Olson from GitHub. In this notebook, Randal is going to go over a basic Python data analysis pipeline from start to finish to show you what a typical data science workflow looks like. In addition to providing code examples, he also hopes to imbue in you a sense of good practices so you can be a more effective — and more collaborative — data scientist. Randal will be following along with the data analysis checklist from …Continue
Added by Emmanuelle Rieuf on July 29, 2016 at 3:30pm — No Comments
Originally posted here, where you can see all the graphics.
There has been much in the news lately about the next wave of MT technology driven by a technology called deep learning and neural nets (DNN). I will attempt to provide a brief layman’s overview about what this is, even though I am barely qualified to do this (but if Trump can run for POTUS then…Continue
Added by Kirti Vashee on July 29, 2016 at 9:30am — No Comments
Under growing pressure to report accurate findings as they interpret increasingly larger amounts of data, researchers are finding it more important than ever to follow sound statistical practices.
For that reason, a team of statisticians including Carnegie Mellon University's Robert E. Kass wrote "Ten Simple Rules for Effective Statistical Practice." Published in PLOS…Continue
Added by Emmanuelle Rieuf on July 28, 2016 at 5:00pm — No Comments
Here are some white papers about Tamr, Lavastorm, Teradata, Rapidminer, Looker, Thingworx, and DataRobot :
Added by Emmanuelle Rieuf on July 28, 2016 at 3:30pm — No Comments
Going somewhere nice for your summer holidays? Somewhere with a nice beach perhaps – Goa, Grand Cayman or Grimsby? Or a bustling city break? Wherever you’re going there’s sure to be long periods where you’ll sit for hours on end with little to do but read, so I thought I’d throw together a few free eBooks for your Kindle to while away the long hours in the airport, in a traffic jam or on the beach.
A mixture of books about data, analysis, statistics and R programming, they’re all very…Continue
Visual Analytics and Data Discovery allow analysis of big data sets to find insights and valuable information. This is much more than just classical Business Intelligence (BI). See this article for more details and motivation: "Using Visual Analytics to Make Better Decisions: the Death Pill Example". Let's take a look at important characteristics to choose the right tool for…Continue
Added by Kai Waehner on July 27, 2016 at 10:00pm — No Comments
Written by sought-after speaker, designer, and researcher Stephanie D. H. Evergreen, Effective Data Visualizationshows readers how to create Excel charts and graphs that best communicate data findings. This comprehensive how-to guide functions as a set of blueprints—supported by research and the author’s extensive experience with clients in industries all over the world—for conveying data in an impactful way. Delivered in Evergreen’s humorous and approachable style, the book covers the…Continue
Added by Emmanuelle Rieuf on July 27, 2016 at 7:00am — No Comments
Added by Dmitry Spodarets on July 26, 2016 at 6:30pm — No Comments
Here's our selection for today. We will continue to post articles from highly respected data scientists in the coming weeks.
Reading some recent blogs, I sense a level of angst among Data Science practitioners about the nature of their field. What exactly IS Data Science - a question that seems to lurk just below the surface . . .
As a young field of study and work, it will naturally take time for a definition of Data Science to crystallize. In the meantime, see if this works for you . . .…Continue
Summary: To ensure quality in your data science group, make sure you’re enforcing a standard methodology. This includes not only traditional data analytic projects but also our most advanced recommenders, text, image, and language processing, deep learning, and AI projects.
A Little HistoryContinue
There are huge numbers of variants of deep architectures as it’s a fast developing field and so it helps to mention other leading algorithms. The list is intended to be comprehensive but not exhaustive since so many algorithms are being developed  ,.
Text classification (a.k.a. text categorization) is one of the most prominent application of Machine Learning. The purpose of text classification is to give conceptual organization to large collection of documents.An interesting application of text classification is to categorize research papers by most suitable conferences. Finding and selecting a suitable academic conference has always been a challenging task especially for…Continue
Added by Aqib Saeed on July 26, 2016 at 3:04am — No Comments
With marketing and advertising gaining more space on the internet, big data analytics are playing a prominent role in following the trends on the market and providing users with key statistics.
Data analysis and statistics traditionally play an important role in analyzing the success of companies and brands in the market.
The growth of internet…Continue
Added by Diana Beyer on July 26, 2016 at 12:00am — No Comments
Many thanks for the retweets and feedback on Part one of this blog
Here is Part Two
Here we extend the discussion and also suggest a practical (and open) way to create a way forward
To recap, lets keep in mind the…Continue
Added by ajit jaokar on July 25, 2016 at 9:54am — No Comments
Added by Emmanuelle Rieuf on July 24, 2016 at 11:30am — No Comments