Data science is a technique that involves inferencing data, development of algorithms, and solving analytically complex problems. It allows you to mine and understand data at a basic and detailed level to solve complex behaviors, trends, and inferences. This technique enables companies to make smarter business decisions by surfacing hidden insights.
- Netflix mines movie-viewing patterns to understand what drives a user's interest. It uses those patterns to make decisions to produce Netflix original series.
- Target Corporations identifies major customer segments within its users and the unique shopping behaviors within those segments. These behaviors help you to guide messages to different market audiences.
Use cases of data science questions
- Hire data analysts who have basic knowledge of building models
Nowadays, challenges in data analytics are being addressed through Machine Learning.
Machine Learning provides you with a platform that enables you to assess the skills of
candidates and hire those who have the knowledge of building models based on predictive
- Hire data science engineers
Hiring skilled candidates for data science engineers is a complex and multidisciplinary task.
You need to test the technical skills of a candidate such as relational databases, big data
platforms, and many more. Machine Learning provides you with a platform that enables you
to evaluate all the skills.
It contains some part of the test data based on which you are evaluated instantly after submission.
It contains entire i.e., 100%, of the test data, based on which the final evaluation (after the challenge gets over) is done.
It retrieves ideal submissions that contain the solution of the offline test cases and compares it to the candidate’s submission.
It is the programming language in which the checker file is written.
Sample expected output file
This file contains the output of the sample dataset.
Expected output file
This file contains the output of the full dataset.