Vive l'analyse!



Who are we? What do we do? What are we here to blog about? Even more surprisingly why do we have a mysterious name such as R-society (Rothschild??) and finally why are we posting by the name of the blog instead by a particular name? These must be the pretty obvious questions that you might be having the moment when you see our name 'R-Society??Well this is exactly what our first blog's going to be about; a deep look into our aim, our ideology, our passion, our ideas, what we represent and perhaps leading finally to a deeper look into 'us'.


 What do two boys in the final year of their engineering (with ample amount of time and energy I must say) with skill, dexterity and passion for data analytics do when they want to share their ideas with the analytics and non-analytics community alike (but are too lazy to visit git-hub) ,what do they do when they want to share their varied projects on a platform where valuable inputs are always welcome leading to the improvement of the project. A common place where new ideas are shared, upcoming analytical advancements are praised and criticized alike. A place where applicative analytics in real life scenarios are talked about and finally let this world realize the potential of data analytics, machine learning and data science. And perhaps, last but not the least to teach the common-folk about the basic understanding of data analytics.







This must seem a little far-fetched but when they say "The world needs to start coding from the age of 10 because it teaches you how to think" we must stress, people need to understand analytics from 16(or any age whatsoever, we just took a random age) because it teaches you how to approach real-life problems and come up with valuable insights and solutions not possible otherwise.


Huff that’s a lot of goals and ideas to achieve, so…what do we do? And the idea pops up why not start a blog? Not like the same traditional types where a single author writes about his experiences and ideas and people comment or share their opinions with them, but a far more intrigued and open society where authors can  actually join and contribute to a blog. Where a number of data science authors can be a part of the same blog. Yes a place where multiple like-minded folk would have the opportunity to express themselves on a common interest. So ladies and gentlemen, Shounak Dutta and R.Rohit welcome you to R-Society, a place where we intend to achieve our aspirations stated above and at the same time ensure the readers enjoy the crazy and entertaining world of data analytics and the fascination it beholds. Aqui` Vamos!!!   
  
So the basic question WHAT WILL BE OUR APPROACH?
We plan to roll out our idea via a set of 4 blogs. This is what each block (constituting 4 blogs) will consist.
We shall be publishing once a week.
The first (of the four) blog will always be about latest advancements in data science, big data analytics and machine learning. This shall constitute of examples of where and how companies and researchers are using data science effectively to make a difference, where the latest advancements are being applied at the same time you read this blog and how AI(Artificial Intelligence) is shaping the future.




The second blog is where we will be sharing our data analytics projects. The entire idea and aim will be vividly described and the source code shall be shared as well the url of websites from where data was collected for the project. We shall be using ‘R’ programming languages for our projects but other authors subsequently joining us will have the complete freedom to choose any programming language of their choice. Readers will be asked to comment on the improvement of the project and they can contribute to the project by downloading the source code provided for the project and tweak it wherever they feel necessary. Moreover the authors who wish to join our blogging society shall put their emails at the comment section at the end of this blog and we shall contact accordingly.

The third blog will be something where we have taken an initiative to teach Data Science using R as the programming language. We shall start from the very basic stage from ‘what is data science’ to subsequently reach advanced topics such as ‘machine learning’. Every blog shall have ample textual content to feed your hunger along with original Coursera videos of Data Science Specialization! for better understanding. Yes people, you will be having access to genuine Coursera materials every week absolutely for free. Now won’t that be cool.


The fourth and final blog of each block shall incorporate the republishing of the project previously published by including the improvements suggested by the readers and authors. It will have a detailed comparison based report on how the previous model is affected by the changes made and an open debate will be welcomed to frame the final model for the project.
So finally here we come at the end of our first blog. This was all about us and how we are planning to do things. A week from now we shall be publishing the first official blog on recent Data Science advancements and technologies. We certainly hope it will be of excellent taste and enjoyable as well. At the end of the day no matter how enthusiastic we are; we won’t be able to reach our goals unless you, yes the data analytics enthusiasts, unless you join the community and help in making R-Society a success. So join us and type your email in the comment section (it will remain discreet) or mail us at rsociety55@gmail.com. And readers see you until next week! Adiós!
 

Comments

Post a Comment

Popular posts from this blog

Stock Market Prediction with R

Image
Time Series Data, QuantMod, ARIMA Now we assume that by reading our last blog your interest in the field of analytics might have peaked a bit. This post of ours would like to increase that a bit further. In today’s blog we’ll deal with Stock Market Prediction using data mining techniques in R. People who have worked in this field might know about this, as it is one of the most basic applications of data mining. Newcomers do not worry. Go through the blog and get an idea of how powerful data analytics is. We are going to start with our course in the very next blog. Additional references for each topic are also provided at the end. Although the project is small, there is a lot of ground to be covered before we actually proceed with the code. Let’s go! Introduction The standard Wikipedia definition of a stock market is “ A   stock market ,   equity market  or   share market  is the aggregation of buyers and sellers (a loose network of economic transactions, not a phy
Keep reading

Sentiment Analysis Using R

Image
Twitter Sentiment Analysis and GST Twitter Authorization and Fetch Twitter Timeline Data Twitter, over the years has become the single place to voice our thoughts. Even though it has a character limitation of 140 characters, the sheer volume of tweets generated is massive. In this post we analyze the reactions to the newly implemented Goods and Services Tax. The code is followed by a step-by-step instruction-cum-explanation part. Do go through it for proper execution. Some quick facts about twitter! Created in March 2006 by Jack Dorsey, Evan Williams, Biz Stone and Noah Glass, Twitter was launched in July 2006 and the first tweet was sent by Jack Dorsey on 21 March 2006. Within 10 years of its operation Twitter has over a billion accounts and 300 million active users. There are over 500 million users who visit the social media website each month without logging in.  500 million tweets are sent every day i.e. every second adds 6000 tweets. This is enou
Keep reading

Introduction to R

Image
Installing R, Packages in R, Data Types in R Let's start the course! But before we do, let us address a few questions. 1.  What is data science ? 2. Why data science? 3. Why R for data science? Data Science Well the name itself gives you an idea but then again, everything must have a complex definition like this:  " Data science is a multidisciplinary blend of  data inference, algorithm development, and technology  in order to solve analytically complex problems ." In simpler words, a field which aims to provide a meaning to vast amounts of complex data. Everyday tons and tons of data is generated from sensors, websites, social media, e-commerce and other sectors. Even though with a larger volume of data you might get better averages, but then there is a lot of noise i.e. useless data as well. To extract useful information to enable decision making is a data scientist's job. 
Keep reading

Stuff That Gets You Interested !

Image
AI, Image Analysis and Convolutional Neural Networks. Analysts! After the overwhelming response received for our introductory blog here we are (quite ahead of schedule) with the very first blog of the first block. It covers recent technological advancements and applications of data science and machine learning. Before you start reading we must inform you that you should continue reading only if you have a basic understanding of the commonly used data-mining and machine learning techniques. This article would actually go slightly above the beginner level at this point of time. However this is just a brief overview and not a tutorial. For readers who are new to data science or machine learning algorithms, do not worry ‘cause in two weeks’ time we will be uploading the very first data science session with Introduction to R and basic R programming overview. Now this is the buzz-word of our generation and perhaps for generations to come. What is it that you keep listening
Keep reading