Types of machine learning
Hlo🙏. The previous article in this series is about the Introduction to Machine Learning. If you had not still read it. Just go through it once. Now I am going to the next topic i.e. Types of machine learning algorithms. These algorithms are widely used in real-world scenarios.
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Transfer Learning
1. Supervised Learning
Labelled data is given to train i.e. dataset with features(input) and along with the labels(output). Let us take the example of translation English speech can be converted to Telugu speech. The key characteristic is this model is trained before with different inputs and outputs. We are going to predict the right output from the given data. Here It can easily translate any language speech. Other examples are spam filtering, ads, and automated machines.
There are two types of the supervised machine learning
Classification
Regression
2. Unsupervised Learning
Unsupervised learning is also called descriptive analytics. It doesn’t have labelled data to train these algorithms. Training using unlabelled data is called Unsupervised learning. From given data, it discovers patterns that help solve clustering or association problems.
Example: News Section by google news, Computer Vision
There are three types of unsupervised learning
Clustering
Dimensionality Reduction
Anomaly Detection
The other types of machine learning algorithms which are quite popular in the modern world are Recommender Systems and Reinforcement Learning.
3. Reinforcement Learning
Reinforcement Learning is based on reward function.
4. Transfer Learning
It is like taking the pre-trained machine learning model and applying it to a similar type of problem that model is pre-trained on.
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