50 New Data Science Resources. Top 50 Data Science Resources: The Best Blogs, Forums, Videos and Tutorials to Learn All about Data Science.
Published by Ngdata.com. This is a short version (summary). The field of data science is constantly evolving and ever-advancing, with new technologies placing more valuable insights in the hands of modern enterprises. How to choose a statistical model. 19 Excellent Free & Open Data Sources for #DataScienceData-Mania by Lillian Pierson. Painless-conjugate-gradient.pdf.
Metronic - Responsive Admin Dashboard Template. Metronic is a responsive and multipurpose admin powered with Twitter Bootstrap 3.3.7 & AngularJS 1.5 frameworks.
Metronic can be used for any type of web applications: custom admin panels, admin dashboards, eCommerce backends, CMS, CRM, SAAS. Metronic has a sleek, clean and intuitive metro & flat balanced design* which makes your next project look awesome and yet user friendly. Metronic has a huge collection of plugins and UI components and works seamlessly on all major web browsers, tablets and phones. We put a lot of love and effort to make Metronic a useful tool for everyone and now Metronic comes with 6 complete admin layouts. We are keen to release continuous long term updates and dozens of new features will be coming soon in the future releases. R-intro.pdf. NSPpart.pdf. New Windows into Law Using Big Data Analytics March 19, 2015. Online R tutorials and Data Science Courses. Quant Education. Book. Customised Social Intelligence Engine. Welcome · Advanced R. Robinson-icebreaker.pdf. R news and tutorials contributed by (573) R bloggers.
The R language, for programmers. IntroductionAssignment and underscoreVariable name gotchasVectorsSequencesTypesBoolean operatorsListsMatricesMissing values and NaNsCommentsFunctionsScopeMisc.Other resources Introduction I have written software professionally in perhaps a dozen programming languages, and the hardest language for me to learn has been R.
The language is actually fairly simple, but it is unconventional. These notes are intended to make the language easier to learn for someone used to more commonly used languages such as C++, Java, Perl, etc. R course notes. Statistics, R, Graphics and Fun. R by example. Basics Reading files Graphs.
Statistics with R. Warning Here are the notes I took while discovering and using the statistical environment R.
However, I do not claim any competence in the domains I tackle: I hope you will find those notes useful, but keep you eyes open -- errors and bad advice are still lurking in those pages... Should you want it, I have prepared a quick-and-dirty PDF version of this document. The old, French version is still available, in HTML or as a single file. You may also want all the code in this document. 1. Quick-R: Home Page. Resources to help you learn and use R. R Tutorial — R Tutorial. 321a Boyd Graduate Studies University of Georgia Athens, Georgia 30602 Introductory Materials¶ These materials are designed to offer an introduction to the use of R.
It is not exhaustive, but is designed to just provide the basics. Thank You! Big Data for Small Businesses. Rvest: easy web scraping with R. Rvest is new package that makes it easy to scrape (or harvest) data from html web pages, inspired by libraries like beautiful soup.
It is designed to work with magrittr so that you can express complex operations as elegant pipelines composed of simple, easily understood pieces. Install it with: install.packages("rvest") rvest in action To see rvest in action, imagine we’d like to scrape some information about The Lego Movie from IMDB. Library(rvest) lego_movie <- html(" To extract the rating, we start with selectorgadget to figure out which css selector matches the data we want: strong span. Lego_movie %>% html_node("strong span") %>% html_text() %>% as.numeric() #>  7.9. Random variables and probability distributions. Probability and statistics.
Learning To Be A Data Scientist. DataTau. The Analytics Edge. Rvest: easy web scraping with R. Web-Scraping: the Basics. Quantifying Memory: Web Scraping: working with APIs. APIs present researchers with a diverse set of data sources through a standardised access mechanism: send a pasted together HTTP request, receive JSON or XML in return.
Today we tap into a range of APIs to get comfortable sending queries and processing responses. Going deeper with dplyr: New features in 0.3 and 0.4 (video tutorial) Introduction to R. 2x1. Download Companion Content for Microsoft Official Courseware. Notebook. E-Learning for Deloitte. Customer Lifetime Value. Beginner's guide to R: Get your data into R. Beginner's guide to R: Get your data into R. Learn how to crunch big data with R. A few years ago I was the CTO and co-founder of a startup in the medical practice management software space.
One of the problems we were trying to solve was how medical office visit schedules can optimize everyone’s time. Too often, office visits are scheduled to optimize the physician’s time, and patients have to wait way too long in overcrowded waiting rooms in the company of people coughing contagious diseases out their lungs. One of my co-founders, a hospital medical director, had a multivariate linear model that could predict the required length for an office visit based on the reason for the visit, whether the patient needs a translator, the average historical visit lengths of both doctor and patient, and other possibly relevant factors. One of the subsystems I needed to build was a monthly regression task to update all of the coefficients in the model based on historical data.
24 beautifully-designed web dashboards that data geeks will love. We live in a world of big (and little) data, and many people have to make sense of numbers as part of their job.
The trouble is that there can be a lot of friction involved when mining the data. This is where dashboards come into play: a well-designed dashboard can save huge amounts of time, helping people to quickly identify the numbers that matter, in order to make insightful observations or to compile reports. Dashboard design is a tricky business. The challenge is to communicate the key numbers in a straightforward way, while allowing users to drill down into the specifics. It is about avoiding clutter, about catering for personalisation, and about the prioritisation of the right metrics. Data dashboards for businesses. E-Learning for Deloitte. Active Data Mining, Data Science blogs. Here are 85 or so active (recently updated) data mining, data science, and machine learning blogs. By Qian Wang. Here are some of the most interesting and regularly-updated blogs on Data Mining, Data Science, and related topics, given in alphabetical order.
If we missed some, please add in comments below. Using Excel to Scrape Twitter. April 23rd, 2012 by Tim Resnik We work with several publishing clients that manage a multitude of Twitter accounts. We frequently run across the problem of spending too much time compiling a large cross section of key Twitter stats for multiple accounts. For example, we have a client that has over 20 Twitter accounts for unique brands unique brands. Analytics, Data Mining, and Data Science.