Solving Real-Life Problems using Machine Learning

Machine Learning problems abound. They make up the core or difficult parts of the software you use on the web or on your desktop every day. Think of the “do you want to follow” suggestions on twitter and the speech understanding in Apple’s Siri.

Below are some examples of machine learning that really ground what machine learning is all about.

Spam Detection

Given email in an inbox, identify those email messages that are spam and those that are not. Having a model of this problem would allow a program to leave non-spam emails in the inbox and move spam emails to a spam folder. We should all be familiar with this example.

Spam Email Classification using ML

Credit Card Fraud Detection

Given credit card transactions for a customer in a month, identify those transactions that were made by the customer and those that were not. A program with a model of this decision could refund those transactions that were fraudulent.

Securing Credit Card Transactions using ML

Digit Recognition

Given a zipcode handwritten on envelopes, identify the digit for each handwritten character. A model of this problem would allow a computer program to read and understand handwritten zip codes and sort envelops by geographic region.

Recognizing Digits for Automation purpose

Speech Understanding

Given an utterance from a user, identify the specific request made by the user. A model of this problem would allow a program to understand and make an attempt to fulfill that request. The famous and useful Google Assistant and iPhone with Siri has this capability.

Speech and Voice Recognition using ML and DL

Face Detection

Given a digital photo album of many hundreds of digital photographs, identify those photos that include a given person. A model of this decision process would allow a program to organize photos by person. Some cameras and software like iPhoto have this capability.

Detection of Faces, as well as Emotions, is possible using ML and DL

Medical Diagnosis

Given the symptoms exhibited in a patient and a database of anonymized patient records, predict whether the patient is likely to have an illness. A model of this decision problem could be used by a program to provide decision support to medical professionals.

Using Computer Vision for detection of abnormalities in the Brain

Thus the uses of Machine Learning and Artificial Intelligence can be extended to almost all parts of our life.

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