Machine Learning Explained
Machine Learning is the process of letting your machine use the data to learn the relationship between predictor variables and the target variable. It is one of the first steps toward becoming a data scientist.
There are two kinds of Machine Learning: supervised, and unsupervised learning. In supervised learning, there are two types: Regression and Classification.
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A machine learning example
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3 Categories of Machine Learning
- Supervised learning: It has a set of labelled data to train the model on. In a way, it means supervising a machine by providing a ton of information about a particular case and giving it the case outcome.
- Unsupervised learning:
Polynomial regression
- Polynomials are algebraic expressions consisting of variables and coefficients.
- Polynomial regressions are the most used in machine learning.
Polynomial regression is a unique case of linear regression:
- You fit a polynomial equ...
Machine learning for autonomous cars
Currently, there is no widely accepted and agreed basis for ensuring that the machine learning algorithms used in the vehicles are safe.
Autonomous vehicles will use artificial intelligence and machine learning to process the data collected from its sensors to help make de...
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