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Building real world books recommendation engine with Python

Using item based collaborative filtering to find similar books
(23 reviews)
90 students
Created by


CourseMarks Score®







Platform: Udemy
Video: 2h 22m
Language: English
Next start: On Demand

Table of contents


Course Description
Learn to build recommendation engine with Collaborative filtering and  popular programming language Python.
Build a strong foundation in Recommendation Systems with this tutorial for beginners.
•Understanding of recommendation systems
•Leverage Collaborative filtering to classify documents
•User Jupyter Notebook for programming
•Use singular value decomposition (SVD) for recommendation engine
A Powerful Skill at Your Fingertips  Learning the fundamentals of recommendation system puts a powerful and very useful tool at your fingertips. Python and Jupyter are free, easy to learn, has excellent documentation.
Jobs in recommendation systems area are plentiful, and being able to learn Collaborative filtering and SVD will give you a strong edge.
Recommendation Systems ares becoming very popular. Amazon, Walmart, Google eCommerce websites are few famous example of recommendation systems in action. Recommendation Systems are vital in information retrieval, upselling and cross selling of products.  Learning Collaborative filtering with SVD will help you become a recommendation system developer which is in high demand.
Big companies like Google, Facebook, Microsoft, AirBnB and Linked In already using recommendation systens with item based collaborative in information retrieval and social platforms. They claimed that using recommendation systems has boosted productivity of entire company significantly.
Content and Overview  
This course teaches you on how to build recommendation systems using open source Python and Jupyter framework.  You will work along with me step by step to build following answers
Introduction to recommendation systems.
Introduction to Collaborative filtering
Build an jupyter notebook step by step using item based collaborative filtering
Build a real world web application to recommend books

What am I going to get from this course?
•Learn recommendations systems and build real world books recommendation engine from professional trainer from your own desk.
•Over 10 lectures teaching you how to build real world recommendation systems
•Suitable for beginner programmers and ideal for users who learn faster when shown.
•Visual training method, offering users increased retention and accelerated learning.
•Breaks even the most complex applications down into simplistic steps.
•Offers challenges to students to enable reinforcement of concepts. Also solutions are described to validate the challenges.

Note: Please note that I am using short documents in this example to illustrate concepts. You can use same code for longer documents as well.

You will learn

✓ At the end of my course students will be able to use the collaborative filtering to recommend books
✓ At the end of my course students will be able to build real world recommendation engine for books


• Students will need to know Python 3 before starting this course

This course is for

• Beginner python developer who are curious to learn about how to apply collaborative filtering to solve real world problems.
Software Mentor
Over 20 years of experience in  programming applications in Fortune 500 companies. I have written 2 books on software design patterns and performance tuning that are published on kindle, nook and ibooks.  So far I have taught react.js, nunit, Chatbot , several courses on machine learning and design patterns.  I have also been working in machine learning area for many years. My passion is leverage my years of experience to teach students in a intuitive and enjoyable manner.
I spent many years at fortune 500 companies, developing and managing the technology that automatically delivers SaaS applications to hundreds of millions of customers.  I have started my own successful company, Evergreen Technologies in 2019, which focuses on online education.
I have over 8000 students spread over 145 countries on Udemy.
I am also available for technical consultation, resume screening and conducting technical interviews of candidates to expedite hiring.
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Platform: Udemy
Video: 2h 22m
Language: English
Next start: On Demand

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