Bye Bye 2014 Welcome 2015

I'll say that the year 2014 was one of the most happening year of my life. I learnt a lot in this year and by the end of this year I am a much more learned person. I got deviated from my ultimate goal but now I am back with full support from my loved ones. In one word I would say that year 2014 was "fantastic".I had a lot of ups and downs and a lot of failures and they taught me how to move on.

I have some goals ready for 2015 I want to complete them as fast as possible.

At present I'll be focusing on Machine Learning because I think it solves the deep desire in me to do something of the type I used to imagine when I was a kid.I wanted to be a scientist and I can make it true if I study data science. Its difficult to follow that path but lets see how much motivated I remain throughout this quest.May be one day I'll be able to call myself a data scientist. 

Wishing everyone a very happy and prosperous new year !

Introduction to Machine Learning

Wishing everyone merry Christmas !

These days I am learning about Machine Learning. The thing that excites me the most about this field is that its like teaching computers how to think like a real human. The computer can develop the ability to do something by learning from the simulation or from the data provided which may be so much difficult if we go through the normal programming.

Machine Learning Algorithms are broadly classified into these two categories -

1. Supervised Learning -
 
                      In this type of learning the computer is given the data with results like right and wrong or classification based results and it is made to learn from it what is correct and what is incorrect or how to classify the result.
       
               It can be further divided into two types -
             
              1. Regression - It is like predicting the continuous value of the asked object like price,quantity,etc,. Ex - Prediction of the stock price from previous month performance of the stock and the market status , estimating the value of the land purchased based on the given data.
 
              2. Classification - It is like predicting a type of outcome out of some finite possible outcomes like predicting the outcome of a football match between Real Madrid and Barcelona whether it will be a draw or Messi's magic will prevail or Ronaldo will seal the victory. In this example no. of possible outcomes are 3. Win,loss and draw

2. Unsupervised Learning - 
      
                  In this type of learning the computer is provided with the data and it is asked to provide some structure in the data provided.Ex - finding the set of people who are having more than say 10 mutual friends on a social networking site or like finding patterns in the genetic structure of two individuals.

There is a famous problem in which the goal is to separate out different type of voices from the recording given. This problem is known as cocktail party problem. There is an algorithm derived for this problem and it took a lot of research to derive it. Surprisingly, now it can be implemented in Octave (A Machine Learning Programming tool) by just a single line of code.

This is what I've learnt.I used to surprise that how photo tagging feature on facebook works.Its accuracy of identifying individuals in the photo is quite good. Now I've the answer. Its ML magic.

Thanks for reading and once again merry Christmas !  

Finally !

After spending a lot of time trying out different things I got a very interesting area to invest my time.
Its Machine Learning ! With a lot of real world applications this is like a dream come true for me . It's just what I needed.

I tried out with android,game development,gui development,etc. I was not that much interested with those things but this is so much interesting that I am taking its course on coursera even at 3 o' clock(night). I don't know whether I'll be able to master it or not but its worth learning it.

Lets see I drive through this part of my journey. One thing is for sure its gonna be interesting damn interesting!!!