The Way To Machine Learning….

Explanation of Machine Learning in Brief

Machine Learning………..

What is Machine Learning?

Ans:- Machine learning is the science (and art) of programming computers so they can learn from data.

Machine learning is the field of study that gives computers the ability to learn without being explicitly programmed.

Or you can say that ,

A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves experience E.

Types of Machine Learning: —

  1. Supervised Learning
  2. Unsupervised Learning
  3. Semisupervised Learning
  4. Reinforcement Learning
  • Supervised Learning:- Supervised learning is the machine learning task of learning a functions that maps an input to an output based on example input-output pairs.It infers a function from labeled training data consisting of a set of training examples. In supervised Learning X and Y both are considered. X means the dependent variable and Y means the independent variable or target variable.
  • Unsupervised Learning:- Unsupervised learning is a type of machine learning algorithm used to draw inferences from datasets consisting of input data without labeled responses. The most common unsupervised learning method is cluster analysis, which is used for exploratory data analysis to find hidden patterns or grouping in data.In Unsupervised Learning only labeled data were used means there is no any target variable.
  • Semi-supervised learning is an approach to machine learning that combines a small amount of labeled data with a large amount of unlabeled data during training. Semi-supervised learning falls between unsupervised learning (with no labeled training data) and supervised learning (with only labeled training data).
  • Reinforcement Learning :- Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning.Reinforcement learning differs from supervised learning in not needing labelled input/output pairs be presented, and in not needing sub-optimal actions to be explicitly corrected. Instead the focus is on finding a balance between exploration (of uncharted territory) and exploitation (of current knowledge).

We will learn in depth one by one all Machine Learning Algorithms in my upcoming blog.

Thank you for Reading.

I am a Data Science Learner.