Project

Google Search Algorithm with Python

Challenging

64 completions

~ 28 hours

4.1

As a result of completing the project, you will implement your own web page ranking algorithm with PageRank as its core. On the way, we will review the basic linear algebra required for this project. You will also get a hands-on experience with the Numpy mathematical package.

Provided by

JetBrains Academy

About

We all use Google. How does Google manage to return a relevant set of web pages for your search in a blink of an eye? In this project, you will have a chance to implement your own ranking algorithm for web pages based on the technology they use in Google – PageRank. You will practice concepts frequently tested in technical interviews at top tech companies.

Graduate project

This project covers the core topics of the Python with Algorithms for Tech Interviews course, making it sufficiently challenging to be a proud addition to your portfolio.

At least one graduate project is required to complete the course.

What you'll learn

Once you choose a project, we'll provide you with a study plan that includes all the necessary topics from your course to get it built. Here’s what awaits you:

Calculate the PageRank with a linear algebra method.

Calculate PageRank with the iterative method up to a given precision.

Calculate PageRank for the given network with the iterative method. Modify the method of calculating PageRank by introducing a damping parameter and check your answer.

Write a function to calculate a PageRank with a damping parameter for an arbitrary network, test it locally and submit your answer.

Write a basic search engine which is using the PageRank algorithm.

Reviews

Paweł Albrycht

2 years ago

4.7

Some practice with eigenvectors, eigenvalues etc. Pretty easy project tbh, one of the easiest I did here

Tomas Dolejsek

2 years ago

3.3

This project shows how PageRank works, but overall it's not that interesting.

Věnceslav Chumchal

4 years ago

5.0

I have learned about the fundamentals of computing PageRank with help of the NumPy library.

4.1

Learners who completed this project within the Python with Algorithms for Tech Interviews course rated it as follows:

Usefulness

4.3

Fun

4.1

Clarity

4.0