Hands-On Data Science with R Dr Graham Williams, PhD (ANU, Machine Learning), BSc (Maths, Hons) Chief Data Scientist, Togaware and Australian Taxation Office Adjunct Professor, Australian National University and University of Canberra International Visiting Professor, Chinese Academy of Sciences Our goal is to provide introductory material to cost effectively kick start an organization's entry into Data Science. To that end, we introduce the use of R for doing Data Science. In addition to the extensive material available on our web site we provide a unique offering of in-situ hands-on training . We offer traditional out-of-office training courses, but we find more effective learning can occur hands-on in-situ. We offer one of the world's leading Data Scientists to work alongside and mentor your staff over one or two weeks. We work confidentially on actual projects, with training "on-the-job" provided by a professional with 30 years experience in the industry and author of the best selling book on Data Mining with Rattle and R . Contact Togaware Training at training@togaware.com for details. Our on-line resources, including Hands-On Data Science , weave together a collection of freely available and open source tools for the Data Scientist. The tools are all part of the R Statistical Software Suite. Each chapter is made up of multiple pages, but each page within a chapter is a one page guide that covers a particular aspect of the topic (hence also refered to as the OnePageR guide). They are a great place to start, before engaging our hands-on training experts. Hands-On Data Science can be worked through as a hands-on guide and then used as a reference guide. Each page aims to be a bite sized chunk for hands-on learning, building on what has gone before. Many chapters also have a lecture pack and a laboratory session where a number of tasks can be completed. The R code sitting behind each chapter is also provided and can be easily run standalone to replicate the material presented in the chapter. The material is always under development ! Chapters will change (and hopefully improve) regularly. Links preceded with a * are more well developed. All of the material is provided under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License allowing access to everyone for any purpose (except commercial) and is provided at no cost. You can assist in helping cover the costs of providing this material through a $40 contribution using PayPal. Your support encourages further development of this resource as does feedback, suggestions, and ideas , which are always welcome. Refer to the Data Mining Survival Guide or my book on Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R) for related material. Many of the initial chapters were developed and tested whilst visiting the Shenzhen Institutes of Advanced Technology as an International Visiting Professor of the Chinese Academy of Sciences. The data used across the chapters is available for download as data.zip . Enjoy! Getting Started as a Data Scientist An Introduction to Data Mining: * Lecture Introducing Data Science, Rattle and R: * Lecture - * Chapter - * R Rattle to R: * Chapter - * R R for the Eager Data Scientist A Template for Preparing Data: * Chapter - * R A Template for Building Models: * Chapter - * R Case Studies: * Chapter - * R Basic R Tips and Tricks Chapter - R Dealing With Data Reading Data into R: * Chapter - * R Exploring and Summarising Data: * Chapter - * R Visualising Data with GGPlot2: * Chapter - * R Transforming Data: * Chapter - * R Descriptive Analytics Cluster Analysis: * Lecture - Chapter - R Association Analysis: * Lecture - Chapter - R Predictive Analytics Decision Trees: * Lecture - * Chapter - * R - * Rattle Ensembles of Decision Trees: * Lecture - * Chapter - * R Support Vector Machines Neural Networks Naive Bayes: Chapter - R Multivariate Adaptive Regression Splines: Chapter - R Evaluating Models: * Chapter - * R Scoring (R) PMML (R) Exporting Models for Deployment Advanced Analytics Text Mining: * Chapter - * R Social Network Analysis: Chapter -R Genetic Programming: Chapter -R Advanced R Strings: Chapter , R Dates and Time: * Chapter - * R Spatial Data * Chapter - * R Big Data * Chapter - * R Exploring Different Plots: Chapter - R Writing Functions: Chapter - R Parallel Processing: Chapter - R Environments: * Chapter - R Expert R Packaging (R) Pulling it Together into a Package Doing R with Style: * Chapter - * R Literate Data Science with KnitR: * Lecture - * Chapter - * R
Just What Is Going On With The Gold In JPMorgan's Vault? Submitted by Tyler Durden on 04/24/2013 21:34 -0400 New York Fed We know that back in early October 2010 , when gold closed at a then record high of $1,320, JPM decided to reopen its previously mothballed precious metal vault due to soaring demand for metal vaulting, thus becoming only the fifth official Comex private gold depository in New York in addition to HSBC, Bank of Nova Scotia, Brinks and MTB (and of course the New York Fed). We also know, courtesy of a Zero Hedge exclusive , that the JPM vault - the largest private gold vault in the world - is located at 1 Chase Manhattan Plaza, and is literally adjacent to the vault of the New York Fed 80 feet, and 5 sublevels, below street level. We know that for a long time the vault held around 2.5 million ounces of eligible ( commercial ) gold, a number which declined only gradually until very recently. We know that the total amount of registered ( investment ) gold has been steady for the past 4 years (after peaking in early 2006). Finally, everyone knows that in the past month gold has experienced a very severe move lower which is still largely unexplained. What many may not know , is that while registered Comex gold has been flat, the amount of eligible gold in Comex warehouses (the distinction between eligible and registered gold can be found here ) in the past several weeks has plunged from nearly 9 million ounces, to just 6.1 million ounces as of today- the lowest since mid-2009. What nobody knows, is why virtually the entire move in warehoused eligible gold is driven exclusively by one firm: JPMorgan, whose eligible gold has collapse from just under 2 million ounces as of the end of 2012 to a nearly record low 402,374 ounces as of today , a drop of 20% in one day, though slightly higher compared to the recent record low hit on April 5 when JPM warehoused commercial gold touched a post-vault reopening low of just over 4 tons, or 142,700 ounces. This happened just days ahead of the biggest ever one-day gold slam down in history. Some questions we would like answers to: What happened to the commercial gold vaulted with JPM, and what was the reason for the historic drawdown? Gold, unlike fiat, is not created out of thin air, nor can it be shred or deleted. Where did the gold leaving the JPM warehouse end up (especially since registered JPM and total Comex gold has been relatively flat over the same period)? Did any of this gold make its way across the street, and end up at the vault of the building located at 33 Liberty street? What happens if and/or when the JPM vault is empty of commercial gold, and JPM receives a delivery notice? Inquiring minds want to know... Average: 5 Your rating: None Average: 5 ( 14 votes) Tweet
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