Basic use of Machine learning
Machine learning is used to build and examine data and statistics. Machine Learning is a proper arrangement of the program that analyses data and learns to predict the conclusion of programs.
It is an advanced step into the guidance of artificial intelligence (AI).
Points to start Machine learning
Under the guidance of machine learning, we will study how to calculate important numbers based on data sets, and it is also helpful to study mathematics and statistics.
It is also helpful to study the different types of python modules to get the desire solution.
It generates functions that are adequate and capable to figure out a solution based on what we have learned.
Data Set
A data set is the combination collection of data. It can be anything from an entire array to a complete database.
In Machine Learning it is simple and natural to work with very broad data sets. In this tutorial, we will try to make it as effortless clear simple and easy as possible to understand the different concepts and approaches of machine learning, and we explain small easy-to-understand data sets.
Example of an array:
[20,28,78,39,71,88,32,80,15,62,53,90]
| StudentName | Class | Age | SerialNumber | Gender |
| Ritu | 10 | 16 | 20 | F |
| Mayank | 9 | 15 | 28 | M |
| Alok | 12 | 18 | 78 | M |
| Reena | 10 | 16 | 39 | F |
| Priyanka | 9 | 16 | 71 | F |
| Darshni | 10 | 16 | 88 | F |
| Karan | 10 | 16 | 32 | M |
| Vishal | 8 | 15 | 80 | M |
| Asim | 10 | 15 | 15 | M |
| Arti | 12 | 18 | 62 | F |
| Vishnu | 10 | 17 | 53 | M |
| Sid | 8 | 14 | 90 | M |
By consider the array, we can calculate that the average value is probably around 20 or 90, and we are also able to resolve the highest value and the lowest value.
And by study the database we can see that most students are from class 10, and the Maximum age of the student is 18 years, but what if we could figure out a student had a gender, just by looking at the other values?
That is what Machine Learning is for! figure out Analyzing data and guess the result!
Data Types
To figure out the data, it is important to know what type of data we are using to work out
We can break the data types into three main class:
- Numerical
- Categorical
- Ordinal
Numerical data are numbers and can break into two numerical division:
Discrete Data, Continuous Data
Discrete Data
- numbers that are defined and bounded in integers. Example: The number of students passing by.
Continuous Data
- numbers that are of absolute value. Example: The Size of a class, or the number of class
Categorical data are values that cannot be consistent and opposed to each other. Example: Number of the student, or any yes/no values.
Ordinal data are like definite and certain data but can be measured up against each other. Example: school grades where A is better than B etc.