- Trending Categories
Data Structure
Networking
RDBMS
Operating System
Java
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Physics
Chemistry
Biology
Mathematics
English
Economics
Psychology
Social Studies
Fashion Studies
Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
What are the applications of Machine Learning?
There are various applications of machine learning which are as follows −
Social media services − Machine learning is an essential role in personalizing news feed to superior advertisement focusing over social media. Facebook needs machine learning to display news feed to the user based on its interests by treating items clicked earlier by that user.
Facebook always takes note of the friends that it can linked with, the profiles that it can visit, interests, workplace, and on the basis of this continuous learning, a file of Facebook users are suggested for us to become friends with.
The Face Recognition nature of Facebook also needs ML to tag the friends in an image. Facebook tests the poses and projections in the images, notices the specific features, and then connects them with the person in the friend's list. The whole process is implemented with the support of ML and is implemented so quickly at the backend that it tags the person as soon as it can upload its picture.
Email spam and malware filtering − Email spam and malware filters have inbuilt machine learning to recognize spam emails. On the basis of emails it is denoted as spam or not, the system understands and recognizes new mail as spam or not, automatically.
Generally, a malware’s code is 90–98% similar to its prior versions. The system security programs that includes machine learning learns the coding design and identify new malware very effectively and provide protection against them.
Search engine result refining − Google and multiple search engines need machine learning to enhance search results for us. Each time it can execute a search, the algorithms at the backend maintain a watch on how it can respond to the results. If it can open the top results and visit on the internet page for long, the search engine consider that the results it showed were in accordance with the query.
Accordingly, if it can reach the second or third page of the search results but do not open someone results, the search engine computes that the results served did not connect requirement. This is the method that machine learning trains itself at the backend to enhance search results.
Online fraud detection − Machine learning is also supporting in creating cyberspace more safe and tracking monetary frauds online. For instance, Paypal is using ML for preservation against money laundering. The company needs a group of ML tools that supports them to compare millions of transactions taking place and differences among legitimate or illegitimate transactions taking place among the buyers and sellers.
Medicine − With the advent of automation, medical data are accessible in electronic structure. The ML algorithms are providing doctors to learn diseases in a best manner by turning the medical data into medical knowledge.
Computational biology − Biologists are collecting multiple data about human DNA. The ML algorithms are supporting them to learn and identify the relationship between several genes and associated human features.
- Related Articles
- 7 Applications of Machine Learning in the Healthcare Industry
- What are the Classifications of Machine Learning?
- What is Machine Learning (ML) and its real-world applications?
- What are the different learning styles in machine learning algorithms?
- What are different components of a machine learning algorithm?
- What are the various challenges for machine learning practitioners?
- What is Machine Learning?
- Machine Learning – The Intelligent Machine
- What are the different kinds of gradient descent algorithms in Machine Learning?
- What is a Machine Learning?
- What are Some Good Python Packages for Machine Learning?
- What are the various useful components of the Python ecosystem for Machine Learning?
- What is Q-learning with respect to reinforcement learning in Machine Learning?
- What are layers in a Neural Network with respect to Deep Learning in Machine Learning?
- Why are Neural Networks needed in Machine Learning?
