Machine Learning Introduction
What is machine learning? Here is the complete introduction to machine learning for complete beginners. Maybe some of you know a little bit or more about Machine Learning(Machine Learning). In this blog, you’ll get a complete machine learning introduction. I have also given some examples of machine learning. Provided some best books of machine learning.
According to Wikipedia: Machine Learning
Here, we will try to define what machine learning is and also know when you want to use machine learning. Even among machine learning practitioners, there isn’t a well-accepted definition of what is and what isn’t machine learning. But let me show you a couple of examples of the ways that people have tried to define it.
Definition Of Machine Learning
Here Arthur Samuel gave an introduction to machine learning in his words,
Machine Learning: Machine Learning is the field of study that gives computers the ability to learn without being explicitly programmed.
This all starts in 1950 by just a checkers game. In 1950, Arthur Samuel wrote a checkers playing program but the amazing thing about this checkers playing program was that Arthur Samuel himself wasn’t a very good checkers player.
Another cool thing is that he had to programmed maybe tens of thousands of games against himself, and by watching what sorts of board positions tended to lead to wins and what sort of board positions tended to lead to losses, the checkers playing program learned over time what are good board positions and what are bad board positions.
This was a result which is remarkable.
Now its turn of Tom Mitchell to give introduction to machine learning,
Machine Learning: 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.
Example: playing chess,
- E = The experience of playing many games of chess
- T = The task of playing chess
- P = The probability of the program which will win the next game of chess
This is the introduction to machine learning definition by Arthur Samuel and Tom Mitchell.
Machine Learning Examples
You have seen in your mailbox, sometimes it goes into spam. It’s because sometimes you might click the Spam button to report some email as spam but not other emails as spam. According to your actions machine learns which mail moves to spam. This is the first example of Machine Learning.
There are some real world examples of machine learning, Have a look:
- Email Spam and Malware Filtering
- Recommendation Engines
- Virtual Personal Assistants
- Self-Driving Cars
- Image Recognition
- Speech Recognition
- Post Ranking On Google and Social Media
- Computer Vision Farming
- Online Fraud Detection
Why Machine Learning Is Important?
Interest in machine learning is due to the same factors that have made data mining and Data analysis more popular than ever. Even availability of volumes and varieties data also you have heard name Big Data.
Machine Learning has It’s own very practical applications that drive the kind of real business results like time saving and as well as money-saving. Customers can be handled with machine learning for small businesses to very big industry level companies.
Machine Learning Books
There are lots of Machine Learning books are available in the market. From those, I pick three best books you can learn for Machine Learning.
1. Machine Learning: A Probabilistic Perspective
Originally published: 2012
Author: Kevin P. Murphy
2. Machine Learning For Dummies
Originally published: 10 May 2016
Authors: Luca Massaron, John Mueller
3. Machine Learning: The New AI
Originally published: 2004
Author: Ethem Alpaydın
This is all about introduction to machine learning.
I have given an introduction to machine learning libraries Have a look at this blog :
Related Post: Best Python Libraries For Machine Learning