Skip to content
  • Linkedin
  • Youtube
  • Pinterest
  • Home
  • Privacy Policy
  • About
  • Contact
Programmingoneonone

Programmingoneonone

Programmingoneonone is a website that publishes daily tutorials, methods, guides, and articles on IT, Education, and technology.

  • Home
  • Human Values
  • DSA
  • IoT Tutorials
  • Interview Questions and Answers
  • Toggle search form
what is machine learning

What is machine learning? – Definition

Posted on 8 May 202010 April 2023 By YASH PAL No Comments on What is machine learning? – Definition

Machine learning: If you are a person who cares about the word called New technology then you must hear about the term called machine learning. and if you seeking the right definition of machine learning then you are in the right place.

So today am going to answer a very big and famous question that is what is machine learning and how it differs from other areas like data science and artificial intelligence?

What you are going to learn

  1. What is machine learning?
  2. Types of machine learning

What is Machine learning? definition

Machine learning is a branch of computer science that deals with different algorithms in different conditions. using these algorithms machines can perform a specific task. we can also use search patterns for performance.

If I say it in simple words then ML is nothing but how we can train a machine so it can learn and perform tasks on its own. 

What is Machine learning using an example?

For example, a robot that can work according to situations without giving outer instructions. and another example is that we all know the site amazon.com which is a very popular eCommerce site. so how Amazon recommended products to their customers? it’s based on machine learning. it uses the customer’s browsing and purchasing history and gives us product suggestions.

Types of Machine Learning

Based on the environment setup there are mainly three types of machine learning models that can be used to train an ML model. 

  1. Supervised Learning
  2. Unsupervised Learning
  3. Reinforcement Learning

Supervised Learning

In supervised learning, we train a model using some pre-trained data. first, we give some inputs which are pre-labeled and then train the model on the desired output. usually, we make rules and just map inputs to the output.

let’s take an example to understand it.

For example: let’s say we are training a model which predicts that whether there is a dog in a given image or not. then to train a model we first give some images as input. and we already know whether there is a dog or not in a particular image. and if the model gives us the wrong output then we train the model on the basis of the desired output. and correct the corresponding output. so the model will be able to take a picture and determine whether or not it contains a dog.  

Unsupervised Learning

In unsupervised learning, we don’t have any pre-labeled data. the model can find them on its own and find the structure in the given input and produce the output. here we use the search patterns.

For example: let’s take the same example. so now using unsupervised learning the model can predict whether there is a dog in pictures or not. eg differences in pixel color or orientations.

Reinforcement Learning

In reinforcement learning, we have a dynamic environment in which we perform different goals.

Example: playing a game against anyone. like a machine playing chess against a man.

There are other categories of machine learning which depend on the output.

Classification

In classification, we divided the inputs into different classes. for example, spam email filtering is a classification technique.

Regression

In Regression, we produce continuously valued outputs. for example, predict the house rent or electricity bill.

Clustering

In clustering, we divide the unlabeled inputs into different groups. for example, customer segmentation.

Density estimation

In DE we find the distribution of inputs in a particular space. like, predicting the result of class students.

Dimensionality reduction

In dimensionality reduction, we simply map the inputs in lower-dimensional space.

Note: if we get large enough data that is pre-labeled. then we use supervised learning. but it is not possible to get the fully labeled data to train a model. so here unsupervised or semi-supervised learning comes into use.

It is the first step we need to choose which type of learning we are going to use to train our model. whether it’s supervised, unsupervised or semi-supervised learning. 

What is semi-supervised learning?

When we use some labeled or unlabeled data set to train our model. then it comes to semi-supervised learning.

After choosing the right learning we also need to choose the proper model and most importantly be able to process data into a pipeline. 

Computer Science Tutorials, Machine Learning Tutorials Tags:computer science, ML

Post navigation

Previous Post: How to Learn Competitive Programming
Next Post: How to Learn Machine Learning using Python

Related Tutorials

Reading input in c programming Reading Input in a C program C Programming Tutorials
The First C Program C Programming Tutorials
Compiling C Programs C Programming Tutorials
History of c programming language HISTORY OF C Programming Language C Programming Tutorials
c character sets C Character Sets C Programming Tutorials
c programming interview questions and answers C Programming Interview Questions and Answers C Programming Tutorials

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Pick your Subject

  • Internet of Things
  • Data Structures/Algorithms
  • Interview Preparation
  • Human Values
  • Java Interview Questions and Answers (2023)
    Thinking of becoming a Java developer? I must say it’s a good choice! Java is continuously named the most popular programming language. And the...

    Learn More “Java Interview Questions and Answers (2023)” »

  • Iot(Internet of things) in healthcare
    IoT in Healthcare
    IoMT (Internet of Medical Things) stands for devices that can collect and exchange data – either with users or other devices via the internet,...

    Learn More “IoT in Healthcare” »

  • four stages of iot solution for industry
    IoT for Industry
    In this post, we are going to learn about use cases of IoT for Industry and four stages for providing IoT solutions. Machine Diagnosis...

    Learn More “IoT for Industry” »

  • Iot for agricultural
    IoT in Agriculture
    IoT technology has realized smart wearables, connected devices, automated machines, and driverless cars. However, in agriculture, the IoT has brought the greatest impact. Amongst the challenges...

    Learn More “IoT in Agriculture” »

  • Iot for logistics
    IoT in Logistics and Supply Chain
    IoT applications for smart logistics and supply chain systems:  Logistics Fleet Tracking  To track the locations of the vehicles in real time, the vehicle...

    Learn More “IoT in Logistics and Supply Chain” »

  • Algorithms Tutorials
  • Basic Programming
  • C Programming Tutorials
  • C++ Tutorials
  • Compiler Design Tutorials
  • Computer Networks Tutorials
  • Computer Organization Tutorials
  • Computer Science Tutorials
  • Data Structures Tutorials
  • DBMS Tutorials
  • Developer Guide
  • Digital Communication
  • Digital Logic Tutorials
  • Internet of Things Tutorials
  • Internet Tutorials
  • Interview questions answers
  • Java Tutorials
  • Javascript Tutorials
  • Machine Learning Tutorials
  • Operating Systems Tutorials
  • Programming Tutorials
  • Projects
  • Tips&Tricks
  • Tools
  • VBScript Tutorials
  • Java Interview Questions and Answers (2023)
    Thinking of becoming a Java developer? I must say it’s a good choice! Java is continuously named the most popular programming language. And the...

    Learn More “Java Interview Questions and Answers (2023)” »

  • Iot(Internet of things) in healthcare
    IoT in Healthcare
    IoMT (Internet of Medical Things) stands for devices that can collect and exchange data – either with users or other devices via the internet,...

    Learn More “IoT in Healthcare” »

  • four stages of iot solution for industry
    IoT for Industry
    In this post, we are going to learn about use cases of IoT for Industry and four stages for providing IoT solutions. Machine Diagnosis...

    Learn More “IoT for Industry” »

  • Iot for agricultural
    IoT in Agriculture
    IoT technology has realized smart wearables, connected devices, automated machines, and driverless cars. However, in agriculture, the IoT has brought the greatest impact. Amongst the challenges...

    Learn More “IoT in Agriculture” »

  • Iot for logistics
    IoT in Logistics and Supply Chain
    IoT applications for smart logistics and supply chain systems:  Logistics Fleet Tracking  To track the locations of the vehicles in real time, the vehicle...

    Learn More “IoT in Logistics and Supply Chain” »

Copyright © 2023 Programmingoneonone.

Powered by PressBook Blog WordPress theme