Prerequisites to study: Introduction to Machine Learning

There are many applications and practical uses of Machine Learning, for example -


We use Machine Learning to diagnose a disease.

The Machine Learning system for this purpose will take certain inputs such as the symptoms of the patient, lab measurements, test results, etc.

The output of the above system would be one of a possible disease or none.

We can also use Machine Learning to determine which treatment can cure the disease of the patient. For doing this we can use data mining techniques to study past medical records, about how past patients have been treated for the same disease and through which we can build a model and using which we can treat future patients.

Computer Vision

We use Machine Learning for object detection i.e. to find what objects appear in an image and where do those objects appear in that image.

Robot Control

We use Machine Learning to design autonomous robots that learn to navigate from their own experience.

Natural Language Processing

Machine Learning is used in NLP as follows –

  • To detect where named entities are mentioned in Natural Language.
  • To detect what facts are expressed in Natural Language.
  • To detect if a product/movie review is positive, negative, or neutral. Also known as Sentiment Analysis.
  • Other applications include Speech Recognition and Machine Translation.


Machine Learning in Finance is used for prediction analysis. Such as to predict if the stock price will rise or fall. Or to predict if a user will click on an advertisement or not, to decide which advertisement to show.

Some other applications

  • Fraud Detection: Credit Cards
  • Determine whether or not someone will default on a home mortgage.
  • Understand consumer sentiment based on unstructured text data.