Machine Learning (ML)

Machine Learning (ML) is a technique that involves training or teaching computers to take decisions or complete actions based on data without explicitly programming them to do so.

Example

Sentiment analysis is a popular technique that companies, brands, campaign managers, etc. are increasingly using to understand and analyze their customers likes and dislikes. This helps them predict what their customers want.

For example:

1. Whenever you read a tweet or a movie review, you are able to understand whether the views that are expressed are positive or negative. The question is — can you teach a computer to determine the sentiment of that piece of text?
2. Whenever Donald Trump makes a speech, the Twitterati goes crazy and tweets both positive and negative statements. Trump’s campaign managers analyze these tweets and determine what the overall sentiment of the populace is.
3. During the World Cup in 2014, Baidu (a Chinese web service company) predicted that Germany would win the world cup even before the match was played! Germany indeed won the World Cup that year.

Important terminology

Offline test cases

It contains entire i.e., 100%, of the test data, based on which the final evaluation (after the challenge gets over) is done.

Online test cases

It contains some part of the test data based on which you are evaluated instantly after submission.

Checker file

It retrieves ideal submission that contains the solution of the offline test cases and compares it to the candidate’s submission.