Hello friends,So in this post we will learn about what is machine learning,what is it’s importance in today’s world,and in which places we use machine learning.
What is Machine learning?
Even among the top pf the machine learning users there is not any accepted definition of what it is and what it is not,but i will show you the couple of definitions that people have given in the past years:
Machine learning definitions:
- Arthur Samuel : Machine learning is a filed of study that gives computers the ability to learn without being explicitly programmed.
- Tom mitchell : According to him machine learning is a well posed learning problem – If we have a some task T and some performance nature P,so a computer program is said to learn from experience E, if it’s performance on T which is measured by P, improves with experience E.
In machine learning we are given a bunch of examples and each one has a number of features,a number of attributes that we can use to describe it and if pick out the right feature and if it’s giving us a right answer then we can classify new examples.
Different Machine Learning Algorithms:
There are many machine learning algorithms exists,but the main two types are what we call supervised learning and unsupervised learning.
Just to understand in a simple lines that in supervised learning the idea is that we are going to teach the computer how to do something,whereas in unsupervised learning we are going it learn it by itself.
Other than this two, reinforcement learning and recommender system are also types of machine learning algorithms,but the most used are above one only.
Supervised Learning
Supervised learning is one of the type of machine learning in which we are given a data set for which we already know what what is the correct output with having the idea that there is a relationship between the i/p and o/p.
Supervised learning problems are categorized into following two problems:
1. regression problem: is the one in which we are trying to predict the results within continuous output,means we are
trying to map our input variables to some continuous function.
2. classification problem: is the one in which we are trying to predict the results in a discrete output(means 0 or
1)means we are trying to map our input variables into some discrete categories.
Unsupervised Learning
In the unsupervised learning,we are given a data set but we are not told what to do with it instead we are just told that here is a data set,can you find some structure in this data set?
In unsupervised learning either we have little or we have no idea of what our results should look like.In this learning we can derive structure from data.
Two types of algorithms mainly exists in unsupervised learning:
1. Clustering algorithm
2. Non-clustering algorithm
Where do we use machine learning?
In following famous works machine learning is used.
- Google’s self-driving cars
- Practical speech recognition
- Effective web search
- Image recognization
- Movie recommendation
This is all about introduction to machine learning,it’s different types and where do we use it?