Building real world books recommendation engine with Python

Building real world books recommendation engine with Python

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.

Using item based collaborative filtering to find similar books

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What 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

Rating: 3.4

Level: Beginner Level

Duration: 2.5 hours

Instructor: Evergreen Technologies