Akhil's Passion

With rest of the speakers/co-ordinators Recently, I got a fantastic opportunity to be a speaker at Google Developers Fest 2015, Trivandrum. It was a wonderful topic I enjoyed learning and sharing. Data Mining with R for Rattle : And here is me on stage:

Mnemonics are cool techniques that are immensely helpful remembering facts. Be it anything from spelling of english words  to  quantum physics , you can make a mnemonic to learn it.  For example:  The spelling of ' SEPARATE ' is one of the the most commonly misspelled word in English language.  "There is A RAT in sep ARAT e" - visualizing and remembering this sentence will help anyone recall the spelling of separate quickly without mistake.  Another example is the spelling of 'necessary' Just remember the sentence 'Shirts have 1 collar and 2 sleeves' to avoid misspelling the number of 'c' and 's'.   It's a clever idea to keep these tricks under your sleeves to impress your friends or teachers with your new exceptional memory powers.  A trick to recall the first10 element of periodic table is to just remember :  "Henry Hester Likes Beer But CanNot Obtain Food Now" Elements: Hydrogen, Helium, Lithium, B

Warning: These are my messy study notes, much better legible notes can be found here  http://onepager.togaware.com 1. A Tour Thru Rattle Transform Tab ( by no means near to the full power of underlying R) Data Mining Tabs - Cluster, Associate Model Log Tab  - Capture the corresponding R command Working from Left to Right on Tabs  Remember to Click Execute Button 'Save' -> Projects save the current state, all models etc. 'Open' Projects can be restored at a later time You can even load it back to R  2. First R Program Load rattle and ggplot2 library(rattle)  # Provides the weather dataset  library(rattle)  # Provides the ggplot() function ggplot -> Grammar of Graphics : Just like english grammar or grammar of a computer language. A result of Hadley's Phd . Look him up to learn more details. Then produce a plot using ggplot() # handsondatascience.com - tips on elegantly writing repeated code ds <- weather 

This is a blog post on a workshop I attended : a three-day hands-on Workshop on Data Mining & Analytics with R at Technopark, Trivandrum on 5th May 2015 Taught by :  Graham Williams - Senior Director and Data Scientist , Australia Graham.Williams@togaware.com http://datamining.togaware.com Read About  - Literate Programming  - Literate Data Mining Philosophy We are not writing program for the computer, it is written to share with other people. Everything that we write should be written for others. We should control the computer not vice versa.  Introducing Data Science Data Mining  Started in around 1989. Lego house - model - > not real but we get an idea. Data mining is all about building such models. Analytics Descriptive Analytics - what happens , suggestions in Amazon Diagnostic Analytics - explain why the above happened Correlation and Causation - Find up people who ended up in hospital after taking a particular d

Chap-1- Meet Hadoop Requirement and adoption in yahoo. A framework that can scale to the web. Map and Reduce acitivity and features like data locality. Can be applied with a variety of algorithms Huge data processing can beat good algorithms Chap-2 - MapReduce The Map Java class and Reducer Java class The Job java class Jobtracker and tasktracker Hadoop reduces the input to input splits or just splits Map tasks write the intermediate output to local disks, so that they can be discarded after use. Outputs of Reduce tasks are stored in HDFS Combiner function can be run on map output, and the combiner functions output forms the input to the reduce function Hadoop streaming proivide hadoop apis in languages other than Java Chap-3 - The Hadoop Distributed Filesystem Fault tolerant solution. Same data written at multiple places. Filesystems that manage the storage across a network of machines are called distributed filesystems. Blocks - a block size is the minim

The Apple Watch launch is almost nearing at the time of writing this article. I'm all excited and ready to submit my first Apple Watch compatible application to the AppStore. I'll write down my learning experience here so that you can publish your own Apple Watch application to the app store . I'll do this step by step, as the work of my current app progress. This article will be updated over time until I reach the final step to see it live in the AppStore. Step 1 : Make the iPhone Part of the Apple Watch An Apple Watch app is not much different from an iPhone app. In fact, it is a sub-part of the main iPhone application running on the iPhone and the Watch App merely acts as the extension of the parent app in the iPhone. So essentially, need an iPhone app anyway. In this scenario, I'm thinking of building an app that will be useful both on iPhone as well as the Apple Watch, instead of solely focusing on the the Apple Watch aspect. The app will be very simple, but al

Apple Watch is soon to release, and being a huge Apple Evangelist, I've been very eager to explore the possibilities of what one can make with these 'Most personal device ever made by Apple'. My hopes are high. I'm in a constant mission to excavate this area at the earliest. And guess what, me and my friends have been working on a couple of interesting 'Apple Watch' things lately: 1. Creating a course - ' Learn Apple Watch Programming Quickly By Examples ' 2. Creating a website for Apple WatchKit Tutorials Both are in beta and will be public soon.  I'm trying to get the latest releases of the WatchKit sdk (which is bundled in Xcode 6.2 beta and higher and is required to build Watch Apps) and trying to publish tutorials on new APIs as and when they come. Following are my objectives with both these online ventures Teach things more by examples and less by theory Convey ideas at the simplest form possible Keep user-interaction at the heart