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 !
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 !
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