How to Build A Recommendation Engine In Python

How to Build A Recommendation Engine In Python, available at $19.99, has an average rating of 4.15, with 14 lectures, 1 quizzes, based on 47 reviews, and has 5103 subscribers.

You will learn about Understand Basic Concepts of a Recommendation Engine Be able to build a simple but functional Recommendation Engine This course is ideal for individuals who are Beginners interested in learning basic machine learning concepts or Python beginners looking for interesting projects It is particularly useful for Beginners interested in learning basic machine learning concepts or Python beginners looking for interesting projects.

Enroll now: How to Build A Recommendation Engine In Python

Summary

Title: How to Build A Recommendation Engine In Python

Price: $19.99

Average Rating: 4.15

Number of Lectures: 14

Number of Quizzes: 1

Number of Published Lectures: 14

Number of Published Quizzes: 1

Number of Curriculum Items: 15

Number of Published Curriculum Objects: 15

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Understand Basic Concepts of a Recommendation Engine
Be able to build a simple but functional Recommendation Engine

Who Should Attend

Beginners interested in learning basic machine learning concepts
Python beginners looking for interesting projects

Target Audiences

Beginners interested in learning basic machine learning concepts
Python beginners looking for interesting projects

Nowadays…Recommendation Engines are everywhere!

Netflix, Amazon and YouTube to name a few.

Then there is the Ultimate Recommendation Engine: Google.

Recommendation Engines help us make choices suited to our personal tastes.

They give us suggestions for products, movies, books, foods and even romantic partners!

Pretty soon, Recommendation Engines will be essential to selling anything and Big Companies are already looking on new ways to use them and for developers and marketeers who understand them.

This course will give you a fundamental, conceptual understanding of how Recommendation Engines work by walking you through building a simple toy Recommendation Engine from scratch using simple math and basic python programming skills.

Taking this course is an easy way to prepare for more advance study as concepts are explained in plain language and code is walked through line by line!

The object of this course is for you to walk away with a solid understanding of the fundamentals behind the Collaborative filtering algorithmused by Netflix to recommend movies to users based on the tastes of other similar users.

So join me inside and make your first big steps towards the future!

Course Curriculum

Chapter 1: Build a Recommendation Engine

Lecture 1: The Problem

Lecture 2: Introduction

Lecture 3: Setting up PythonAnywhere Account

Lecture 4: What is a Recommender Engine

Lecture 5: What is Collaborative Filtering Algorithm

Lecture 6: What is Euclidean Distance and Why Do We Care?

Lecture 7: Euclidean Distance Method with Python

Lecture 8: Finding Similarity

Lecture 9: Recommendation Function Concept

Lecture 10: Find Commonly Reviewed Items

Lecture 11: Finding Critic Similarity

Lecture 12: Compiling Similarity Scores

Lecture 13: Making Recommendations

Lecture 14: Conclusion

Instructors

John Williams
Entrepreneur, Software Developer, Speaker and Coach

Rating Distribution

1 stars: 3 votes
2 stars: 6 votes
3 stars: 12 votes
4 stars: 13 votes
5 stars: 13 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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