---
layout: post
title: Machine Learning - Intro
excerpt: "Just an (in)formal introduction"
modified: 2013-05-31
tags: [machine learning]
comments: true
image:
  feature: sample-image-5.jpg
  credit: WeGraphics
  creditlink: http://wegraphics.net/downloads/free-ultimate-blurred-background-pack/
---

What is machine learning? Here's a definition:

> A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.

This is a bit complicated definition. To simplify, let's take the example of playing checkers.

* E -> Experience of playing checkers games
* T -> The task of playing checkers
* P -> The probability that the program will win the next game

There are mainly two different types of learnings

#### Supervised Learning

In supervised learning, we have a data set and knowledge about how the output looks like. We are aware that there is a relationship between the input and the output. Supervised learning problems are of two types:

* Classification Problems
* Regression Problems

#### Unsupervised Learning

In unsupervised learning, we have a set of data. We have a little or no idea about how the output will look like.

---
layout: post
title: Machine Learning - Intro
excerpt: "Introduction to machine learning"
modified: 2013-05-31
tags: [machine learning]
comments: true
image:
  feature: sample-image-5.jpg
  credit: WeGraphics
  creditlink: http://wegraphics.net/downloads/free-ultimate-blurred-background-pack/
---

What is machine learning? Here's a definition:

> A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.

This is a bit complicated definition. To simplify, let's take the example of playing checkers.

* E -> Experience of playing checkers games
* T -> The task of playing checkers
* P -> The probability that the program will win the next game

There are mainly two different types of learnings

#### Supervised Learning

In supervised learning, we have a data set and knowledge about how the output looks like. We are aware that there is a relationship between the input and the output. Supervised learning problems are of two types:

* Classification Problems
* Regression Problems

#### Unsupervised Learning

In unsupervised learning, we have a set of data. We have a little or no idea about how the output will look like.

Change description for post 2
Change description for post 2
