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A 3D Printed World

From http://en.wikipedia.org/wiki/3D_printing

Additive manufacturing or 3D printing[1] is a process of making three dimensional solid objects from a digital model. 3D printing is achieved using additive processes, where an object is created by laying down successive layers of material.[2] 3D printing is considered distinct from traditional machining techniques (subtractive processes) which mostly rely on the removal of material by drilling, cutting etc.

A world without factories , or atleast not as many. Where the only thing to be bought is design and raw material . Direct from the creators to the consumers.

Imagine 2025 – with the latest generation of 3 D printers. You browse though online catalogs, select designs  for furniture, accessories, clothes. Click buy and then print.

No more inventory planning ( except for the raw material wood,synthetic,cloth, plastic or better still an intermediate that can be done in all of these). Everything is bio-degradable in this new world of 3D printers.

That future is closer than you think! No more Made in China vs Made in USA

Everything will be made at home! designed by artists! delivered by Internet.

This is probably how they will shift manufacturing back to the rest of the planet to the First World, as both China and India are lagging behind in understanding the ramifications of mass produced 3D printers. 3D printers could do to factories what automatic washing machines did to laundry.

  1. http://mashable.com/2012/07/17/3d-printing-continuum-fashion/
  2. http://singularityhub.com/2012/04/23/3d-printing-robot-produces-chairs-and-tables-from-recycled-waste/
  3. http://www.wired.com/dangerroom/2012/08/3d-weapons/

Interview Rob J Hyndman Forecasting Expert #rstats

Here is an interview with Prof Rob J Hyndman who has created many time series forecasting methods and authored books as well as R packages on the same.

Ajay -Describe your journey from being a student of science to a Professor. What were some key turning points along that journey?
 
Rob- I started a science honours degree at the University of Melbourne in 1985. By the end of 1985 I found myself simultaneously working as a statistical consultant (having completed all of one year of statistics courses!). For the next three years I studied mathematics, statistics and computer science at university, and tried to learn whatever I needed to in order to help my growing group of clients. Often we would cover things in classes that I’d already taught myself through my consulting work. That really set the trend for the rest of my career. I’ve always been an academic on the one hand, and a statistical consultant on the other. The consulting work has led me to learn a lot of things that I would not otherwise have come across, and has also encouraged me to focus on research problems that are of direct relevance to the clients I work with.
I never set out to be an academic. In fact, I thought that I would get a job in the business world as soon as I finished my degree. But once I completed the degree, I was offered a position as a statistical consultant within the University of Melbourne, helping researchers in various disciplines and doing some commercial work. After a year, I was getting bored doing only consulting, and I thought it would be interesting to do a PhD. I was lucky enough to be offered a generous scholarship which meant I was paid more to study than to continue working.
Again, I thought that I would probably go and get a job in the business world after I finished my PhD. But I finished it early and my scholarship was going to be cut off once I submitted my thesis. So instead, I offered to teach classes for free at the university and delayed submitting my thesis until the scholarship period ran out. That turned out to be a smart move because the university saw that I was a good teacher, and offered me a lecturing position starting immediately I submitted my thesis. So I sort of fell into an academic career.
I’ve kept up the consulting work part-time because it is interesting, and it gives me a little extra money. But I’ve also stayed an academic because I love the freedom to be able to work on anything that takes my fancy.
Ajay- Describe your upcoming book on Forecasting.
 
Rob- My first textbook on forecasting (with Makridakis and Wheelwright) was written a few years after I finished my PhD. It has been very popular, but it costs a lot of money (about $140 on Amazon). I estimate that I get about $1 for every book sold. The rest goes to the publisher (Wiley) and all they do is print, market and distribute it. I even typeset the whole thing myself and they print directly from the files I provided. It is now about 15 years since the book was written and it badly needs updating. I had a choice of writing a new edition with Wiley or doing something completely new. I decided to do a new one, largely because I didn’t want a publisher to make a lot of money out of students using my hard work.
It seems to me that students try to avoid buying textbooks and will search around looking for suitable online material instead. Often the online material is of very low quality and contains many errors.
As I wasn’t making much money on my textbook, and the facilities now exist to make online publishing very easy, I decided to try a publishing experiment. So my new textbook will be online and completely free. So far it is about 2/3 completed and is available at http://otexts.com/fpp/. I am hoping that my co-author (George Athanasopoulos) and I will finish it off before the end of 2012.
The book is intended to provide a comprehensive introduction to forecasting methods. We don’t attempt to discuss the theory much, but provide enough information for people to use the methods in practice. It is tied to the forecast package in R, and we provide code to show how to use the various forecasting methods.
The idea of online textbooks makes a lot of sense. They are continuously updated so if we find a mistake we fix it immediately. Also, we can add new sections, or update parts of the book, as required rather than waiting for a new edition to come out. We can also add richer content including video, dynamic graphics, etc.
For readers that want a print edition, we will be aiming to produce a print version of the book every year (available via Amazon).
I like the idea so much I’m trying to set up a new publishing platform (otexts.com) to enable other authors to do the same sort of thing. It is taking longer than I would like to make that happen, but probably next year we should have something ready for other authors to use.
Ajay- How can we make textbooks cheaper for students as well as compensate authors fairly
 
Rob- Well free is definitely cheaper, and there are a few businesses trying to make free online textbooks a reality. Apart from my own efforts, http://www.flatworldknowledge.com/ is producing a lot of free textbooks. And textbookrevolution.org is another great resource.
With otexts.com, we will compensate authors in two ways. First, the print versions of a book will be sold (although at a vastly cheaper rate than other commercial publishers). The royalties on print sales will be split 50/50 with the authors. Second, we plan to have some features of each book available for subscription only (e.g., solutions to exercises, some multimedia content, etc.). Again, the subscription fees will be split 50/50 with the authors.
Ajay- Suppose a person who used to use forecasting software from another company decides to switch to R. How easy and lucid do you think the current documentation on R website for business analytics practitioners such as these – in the corporate world.
 
Rob- The documentation on the R website is not very good for newcomers, but there are a lot of other R resources now available. One of the best introductions is Matloff’s “The Art of R Programming”. Provided someone has done some programming before (e.g., VBA, python or java), learning R is a breeze. The people who have trouble are those who have only ever used menu interfaces such as Excel. Then they are not only learning R, but learning to think about computing in a different way from what they are used to, and that can be tricky. However, it is well worth it. Once you know how to code, you can do so much more.  I wish some basic programming was part of every business and statistics degree.
If you are working in a particular area, then it is often best to find a book that uses R in that discipline. For example, if you want to do forecasting, you can use my book (otexts.com/fpp/). Or if you are using R for data visualization, get hold of Hadley Wickham’s ggplot2 book.
Ajay- In a long and storied career- What is the best forecast you ever made ? and the worst?
 
 Rob- Actually, my best work is not so much in making forecasts as in developing new forecasting methodology. I’m very proud of my forecasting models for electricity demand which are now used for all long-term planning of electricity capacity in Australia (see  http://robjhyndman.com/papers/peak-electricity-demand/  for the details). Also, my methods for population forecasting (http://robjhyndman.com/papers/stochastic-population-forecasts/ ) are pretty good (in my opinion!). These methods are now used by some national governments (but not Australia!) for their official population forecasts.
Of course, I’ve made some bad forecasts, but usually when I’ve tried to do more than is reasonable given the available data. One of my earliest consulting jobs involved forecasting the sales for a large car manufacturer. They wanted forecasts for the next fifteen years using less than ten years of historical data. I should have refused as it is unreasonable to forecast that far ahead using so little data. But I was young and naive and wanted the work. So I did the forecasts, and they were clearly outside the company’s (reasonable) expectations, and they then refused to pay me. Lesson learned. It’s better to refuse work than do it poorly.

Probably the biggest impact I’ve had is in helping the Australian government forecast the national health budget. In 2001 and 2002, they had underestimated health expenditure by nearly $1 billion in each year which is a lot of money to have to find, even for a national government. I was invited to assist them in developing a new forecasting method, which I did. The new method has forecast errors of the order of plus or minus $50 million which is much more manageable. The method I developed for them was the basis of the ETS models discussed in my 2008 book on exponential smoothing (www.exponentialsmoothing.net)

. And now anyone can use the method with the ets() function in the forecast package for R.
About-
Rob J Hyndman is Pro­fessor of Stat­ist­ics in the Depart­ment of Eco­no­met­rics and Busi­ness Stat­ist­ics at Mon­ash Uni­ver­sity and Dir­ector of the Mon­ash Uni­ver­sity Busi­ness & Eco­nomic Fore­cast­ing Unit. He is also Editor-in-Chief of the Inter­na­tional Journal of Fore­cast­ing and a Dir­ector of the Inter­na­tional Insti­tute of Fore­casters. Rob is the author of over 100 research papers in stat­ist­ical sci­ence. In 2007, he received the Moran medal from the Aus­tralian Academy of Sci­ence for his con­tri­bu­tions to stat­ist­ical research, espe­cially in the area of stat­ist­ical fore­cast­ing. For 25 years, Rob has main­tained an act­ive con­sult­ing prac­tice, assist­ing hun­dreds of com­pan­ies and organ­iz­a­tions. His recent con­sult­ing work has involved fore­cast­ing elec­tri­city demand, tour­ism demand, the Aus­tralian gov­ern­ment health budget and case volume at a US call centre.

New Free Online Book by Rob Hyndman on Forecasting using #Rstats

From the creator of some of the most widely used packages for time series in the R programming language comes a brand new book, and its online!

This time the book is free, will be updated and 7 chapters are ready (to read!)

. If you do forecasting professionally, now is the time to suggest your own use cases to be featured as the book gets ready by end- 2012. The book is intended as a replace­ment for Makri­dakis, Wheel­wright and Hyn­d­man (Wiley 1998).

http://otexts.com/fpp/

The book is writ­ten for three audi­ences:

(1) people find­ing them­selves doing fore­cast­ing in busi­ness when they may not have had any for­mal train­ing in the area;

(2) undergraduate stu­dents study­ing busi­ness;

(3) MBA stu­dents doing a fore­cast­ing elec­tive.

The book is dif­fer­ent from other fore­cast­ing text­books in sev­eral ways.

  • It is free and online, mak­ing it acces­si­ble to a wide audience.
  • It is con­tin­u­ously updated. You don’t have to wait until the next edi­tion for errors to be removed or new meth­ods to be dis­cussed. We will update the book frequently.
  • There are dozens of real data exam­ples taken from our own con­sult­ing prac­tice. We have worked with hun­dreds of busi­nesses and orga­ni­za­tions help­ing them with fore­cast­ing issues, and this expe­ri­ence has con­tributed directly to many of the exam­ples given here, as well as guid­ing our gen­eral phi­los­o­phy of forecasting.
  • We empha­sise graph­i­cal meth­ods more than most fore­cast­ers. We use graphs to explore the data, analyse the valid­ity of the mod­els fit­ted and present the fore­cast­ing results.

A print ver­sion and a down­load­able e-version of the book will be avail­able to pur­chase on Ama­zon, but not until a few more chap­ters are written.

Contents

(Ajay-Support the open textbook movement!)

If you’ve found this book helpful, please consider helping to fund free, open and online textbooks. (Donations via PayPal.)

Look for yourself at http://otexts.com/fpp/

 

Online Education takes off

Udacity is a smaller player but welcome competition to Coursera. I think companies that have on demand learning programs should consider donating a course to these online education players (like SAS Institute for SAS , Revolution Analytics for R, SAP, Oracle for in-memory analytics etc)

Any takers!

http://www.udacity.com/

 

Coursera  is doing a superb job with huge number of free courses from notable professors. 111 courses!

I am of course partial to the 7 courses that are related to my field-

https://www.coursera.org/

 

 

R for Business Analytics- Book by Ajay Ohri

So the cover art is ready, and if you are a reviewer, you can reserve online copies of the book I have been writing for past 2 years. Special thanks to my mentors, detractors, readers and students- I owe you a beer!

You can also go here-

http://www.springer.com/statistics/book/978-1-4614-4342-1

 

R for Business Analytics

R for Business Analytics

Ohri, Ajay

2012, 2012, XVI, 300 p. 208 illus., 162 in color.

Hardcover
Information

ISBN 978-1-4614-4342-1

Due: September 30, 2012

(net)

approx. 44,95 €
  • Covers full spectrum of R packages related to business analytics
  • Step-by-step instruction on the use of R packages, in addition to exercises, references, interviews and useful links
  • Background information and exercises are all applied to practical business analysis topics, such as code examples on web and social media analytics, data mining, clustering and regression models

R for Business Analytics looks at some of the most common tasks performed by business analysts and helps the user navigate the wealth of information in R and its 4000 packages.  With this information the reader can select the packages that can help process the analytical tasks with minimum effort and maximum usefulness. The use of Graphical User Interfaces (GUI) is emphasized in this book to further cut down and bend the famous learning curve in learning R. This book is aimed to help you kick-start with analytics including chapters on data visualization, code examples on web analytics and social media analytics, clustering, regression models, text mining, data mining models and forecasting. The book tries to expose the reader to a breadth of business analytics topics without burying the user in needless depth. The included references and links allow the reader to pursue business analytics topics.

 

This book is aimed at business analysts with basic programming skills for using R for Business Analytics. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. Business analytics (BA) refers to the field of exploration and investigation of data generated by businesses. Business Intelligence (BI) is the seamless dissemination of information through the organization, which primarily involves business metrics both past and current for the use of decision support in businesses. Data Mining (DM) is the process of discovering new patterns from large data using algorithms and statistical methods. To differentiate between the three, BI is mostly current reports, BA is models to predict and strategize and DM matches patterns in big data. The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy.

Content Level » Professional/practitioner

Keywords » Business Analytics – Data Mining – Data Visualization – Forecasting – GUI – Graphical User Interface – R software – Text Mining

Related subjects » Business, Economics & Finance – Computational Statistics – Statistics

TABLE OF CONTENTS

Why R.- R Infrastructure.- R Interfaces.- Manipulating Data.- Exploring Data.- Building Regression Models.- Data Mining using R.- Clustering and Data Segmentation.- Forecasting and Time-Series Models.- Data Export and Output.- Optimizing your R Coding.- Additional Training Literature.- Appendix

Apps for Google Drive

I kind of liked the fact that Google Drive has a lot of apps already- even though it is quite young.

Especially the mechanical engineer in me liked the AutoCAD app and the video editing apps, the online bitcoin wallet, free project scheduling app, the cloud’s first (?) open office document reader and etc

Developers would especially like playing with the OAuth Playground app for Google Drive on the Google Chrome platform.

Check out  for yourself.

https://chrome.google.com/webstore/category/collection/drive_apps

Possible Digital Disruptions by Cyber Actors in USA Electoral Cycle

Some possible electronic disruptions  that threaten to disrupt the electoral cycle in United States of America currently underway is-

1) Limited Denial of Service Attacks (like for 5-8 minutes) on fund raising websites, trying to fly under the radar of network administrators to deny the targeted  fundraising website for a small percentage of funds . Money remains critical to the world’s most expensive political market. Even a 5% dropdown in online fund-raising capacity can cripple a candidate.

2)  Limited Man of the Middle  Attacks on ground volunteers to disrupt ,intercept and manipulate communication flows. Basically cyber attacks at vulnerable ground volunteers in critical counties /battleground /swing states (like Florida)

3) Electro-Magnetic Disruptions of Electronic Voting Machines in critical counties /swing states (like Florida) to either disrupt, manipulate or create an impression that some manipulation has been done.

4) Use search engine flooding (for search engine de-optimization of rival candidates keywords), and social media flooding for disrupting the listening capabilities of sentiment analysis.

5) Selected leaks (including using digital means to create authetntic, fake or edited collateral) timed to embarrass rivals or influence voters , this can be geo-coded and mass deployed.

6) using Internet communications to selectively spam or influence independent or opinionated voters through emails, short messaging service , chat channels, social media.

7) Disrupt the Hillary for President 2016 campaign by Anonymous-Wikileak sympathetic hacktivists.

 

 

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