Machine Learning

Machine Learning is making the computer learn from studying data and statistics.

Machine learning is a step towards Artificial Intelligence (which sort form is AI).

It is the program that analyzes data and learns to make prediction the result.

Where To Start?

In this tutorial we will go back to math and study statistics, and how to calculate significant numbers based on the data set.

We will learn that how to use different Python modules to gets the answers we required.

And we'll learn how to act so that we're able to predict the outcome based on what we've learned.

Data Set

In the mind of a computer, a data set is any collection of data. It can be anything from an array to a complete database.

Example of an array:

[99,86,103,87,94,78,77,85,86,86,87,88,111]

Data Types

In order to analyze data, it is important to know what kind of data we are tackling with.

We can split the data types into three main categories:

Numerical Categorical Ordinal

Numerical data are numbers, and can be split into two numerical categories:

Discrete Data - numbers that are limited to integers. Example: The number of cars passing by. Continuous Data - numbers that are of infinite value. Example: The price of an item, or the size of an item

Categorical data are values that cannot be measured up against each other. Example: a color value, or any yes/no values.

Normal data are such hierarchical data, but can be measured against each other. Example: School grades where A is better than B and so on.

By knowing the data type of your data source, you will be able to know what technique to use when analyzing them.