Skip to content
DATA SCIENCE
  • English
    • Deutsch
    • Français
    • Español
    • Português
    • Italiano
    • Nederlands
    • Polski
    • Русский
  • Artificial Intelligence
  • Computer programming
  • Computer Vision
  • Machine Learning
  • Mathematics & statistics
  • Natural Language Processing
  • Wiki
DATA SCIENCE
  • English
    • Deutsch
    • Français
    • Español
    • Português
    • Italiano
    • Nederlands
    • Polski
    • Русский
  • Artificial Intelligence
  • Computer programming
  • Computer Vision
  • Machine Learning
  • Mathematics & statistics
  • Natural Language Processing
  • Wiki

Machine Learning

Machine learning (ML) is a subset of artificial intelligence. It focuses on the study of computer algorithms that improve automatically on their own, through experience. These algorithms are used in a large variety of different applications, from computer vision to mathematical optimizations. ML algorithms are necessary when it is difficult or not feasible to develop conventional algorithms to perform a necessary task.

The four main types of ML include:

  • Supervised machine learning algorithms that can apply what has already been learned in previous situations to new data using labeled examples to predict possible future events.
  • Unsupervised machine learning algorithms are used when the information used to train the model is neither classified nor labeled. Unsupervised learning can infer a function to describe a hidden structure from unlabeled data. Likewise, the system isn’t intended to figure out the right output, but it explores the data and can draw inferences from datasets to describe hidden structures from unlabeled data.
  • Semi-supervised machine learning algorithms fall in between supervised and unsupervised learning. They use both labeled and unlabeled data for training, skewing towards unlabeled data. Semi- supervised learning is selected when the acquired labeled data requires qualified and appropriate resources to train/learn from that. Otherwise, unlabeled data acquisition typically needs no additional capital.
  • Reinforcement machine learning algorithms is a learning method that produces actions and discovers errors through its environment. This method allows the algorithm to automatically understand behavior within a specific context in order to maximize its performance. Reward feedback is needed for the agent to understand which action is best, and this is known as a reinforcement signal.
Machine Learning

Kullback-Leibler Divergence Explained

All the time in Likelihood and Measurements we’ll supplant watched information or a mind-boggling circulations with a less difficult, approximating dissemination. KL Dissimilarity encourages...

by Data Science Team 2 years agoMay 3, 2020
Machine Learning

A Beginner’s Guide to Generative Adversarial Networks (GANs)

You might not think that programmers are artists, but programming is a particularly creative profession. It’s logic-based creativity. – John Romero Generative Adversarial Network...

by Data Science 2 years agoJanuary 14, 2021
Languages
Posts navigation
  • 1
  • …
  • 5
  • 6
  • 7
DATA SCIENCE . EU
The #1 Multilingual Source for DataScience
  • English
    • Deutsch
    • Français
    • Español
    • Português
    • Italiano
    • Nederlands
    • Polski
    • Русский
  • Artificial Intelligence
  • Computer programming
  • Computer Vision
  • Machine Learning
  • Mathematics & statistics
  • Natural Language Processing
  • Wiki
This website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish. Cookie settingsACCEPT
Privacy & Cookies Policy

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these cookies, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may have an effect on your browsing experience.
Necessary
Always Enabled
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Non-necessary
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.
SAVE & ACCEPT