Recommendation Engine Bootcamp with 3 Capstone Projects

Master recommendation systems Industry Projects using using modern recommendation techniques and methodologies

4.40 (154 reviews)
Udemy
platform
English
language
Data Science
category
14,757
students
4.5 hours
content
Mar 2022
last update
$64.99
regular price

What you will learn

Learn about the different types of Recommender Systems.

Learn about Content based recommendation system.

Learn about Collaborative based filtering.

Learn about Singular Value Decomposition.

Learn recommending movies, books using the recommendation system.

Learn about Surprise Library for recommendation systems.

Learn how to use Correlation for Recommending similar Movies and Genres.

Learn how to use different Techniques used for Imputing Missing Values.

Practice Quizzes and Exercises of this course.

Project Course 1: Movie Recommender Systems.

Project Course 2: Open Jobs Analyzer and Recommendation System.

Project Course 3: Books Recommendation Engine.

Description

Welcome to the best online course on Recommendation Engine.

Master various recommendation engines including Content-based filtering, collaborative filtering, Singular value decomposition.

Recommender systems aim to predict users' interests and recommend product items that quite likely are interesting for them.

A recommendation engine is a type of data filtering tool using machine learning algorithms to recommend the most relevant items to a particular user or customer.

It operates on the principle of finding patterns in consumer behavior data, which can be collected implicitly or explicitly.


This course gives you a thorough understanding of the Recommendation systems.


In this course, you will cover

  • Introduction to Recommendation Engine.

  • Use cases of recommender systems.

  • Content-based filtering.

  • Filtering movies based on genres.

  • User-based collaborative filtering.

  • Item-based collaborative filtering.

  • Singular value decomposition using Surprise library.

  • and much, much more!


Not only this, you will also work on three very exciting projects such as


  • Project Course 1: Movie Recommender Systems

  • Project Course 2: Open Jobs Analyzer and Recommendation System

  • Project Course 3: Books Recommendation Engine.


I am always available to answer your questions and help you along your data science journey. See you in class!

You will learn to create a movie recommendation engine as well as a book recommendation engine and Open job analyzer system.

It will be fun working on such exciting projects.

You will see how easy it is to recommend new books or movies based on the user's past preferences.

Instructor Support - Quick Instructor Support for any queries.

I'm looking forward to see you in the course!


I guarantee you will love this course.

All the resources used in this course will be shared with you.

Don’t wait and Enroll now.

Content

Introduction to Recommendation System

Introduction to Recommender systems
What are it's Use Cases
Types of Recommender Systems
Evaluating Recommender Systems

Content Based Filtering

Introduction to Content Based Filtering
Preprocessing the Data for Content Based Filtering
Filtering Movies Based on Genres
Introduction to Transactional Encoder
Recommending Similar Movies to Watch
Quiz on Content Based Filtering
Quiz Solution

Collaborative Based Filtering

Introduction to Collaborative Filtering
Preprocessing the Data for Collaborative Filtering
Implementation of User Based Collaborative Filtering
Interpreting the Results obtained from User Based Filtering
Implementation of Item Based Collaborative Filtering
Quiz on Collaborative Based Filtering
Quiz Solution

Singular Value Decomposition

Introduction to SVD
Implementing SVD using Surprise
Interpreting Results Obtained from SVD
Comparing Content, and Collaborative Based Filtering
Quiz on Singular Value Decomposition
Quiz Solution

Case Studies from Giants

Case Study for Netflix
Case Study for Youtube

Movie Recommender Systems

Setting up the Environment
Taking a Deep Dive into the Dataset
Understanding the Problem Statement
Missing Values Imputation
Top 10 Profitable Movies
Manipulating the Duration and Language Column
Extracting the Movie Genres
Top 10 Most Popular Movies on Social Media
Analyzing Which Genre is Most Bankable?
Loss and Profit Analysis on English and Foreign Movies
Gross Comparison of Long and Short Movies
Association between IMDB Rating and Duration
Comparing Critically acclaimed Actors
Top Movies based on Gross, and IMDB
Recommending Movies based on Languages and Actors
Recommending Similar Genres and Movies
Key Takeaways from this Project
Quiz on Movie Recommender Systems

Open Jobs Analyzer and Recommendation System

Understanding the Problem Statement
Setting up the Environment
Taking a Deep Dive into the Job Dataset
Analyzing the Job Metrices
Finding Important Metrics for Salary
Taking a Deep Dive at the Naukri Dataset
Finding Locations with Highest Job Vacancies
Analyzing the Experience required for Jobs
Most Demanded Degrees for Jobs
Analyzing the Industries with highest no. of Jobs
Analyzing the Top Skills required for Jobs
Cleaning the Rest of the Dataset
Gathering Vital Information from the Dataset
Making a Function to Search for Jobs
Understanding Relation between Industries and Education
Key Takeaways and Findings from the Project
Quiz on Open Jobs Analyzer and Recommendation System

Outro Section

Conclusion
How to Get Your Certificate of Completion

Bonus Section

Bonus Lecture

Screenshots

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Reviews

Shubhanshu
February 10, 2023
This course is simply awesome. The content was good and easy to understand. The interesting thing is that anyone can learn simply from beginner-level to expert-level topics. You can get a very strong knowledge of recommender systems with this course. The projects provided in the course are really helpful to understand real-world examples. Thank you for the course!
Emma
January 3, 2023
Seriously poor service from Data is Good and from Udemy. No hours of contact or message me function from Data is Good. The course content seemed good value for money but none of the commands the lecturer stated actually enabled me to install the notebook on my computer and when I tried to ask for support from Udemy they said they have no control over when course convenors respond. My only recourse was to message Data is Good on Facebook and they responded three days later saying they had scaled back their work with Udemy they could not support me and they offered me a course costing, no exaggeration, exactly x100 what I paid for the one they'd failed to support me on. WHat a waste of a day. Livid
Arjun
October 31, 2022
This course was really helpful! The content taught is really good and has helped me in understanding recommender systems in an interesting way. The course was comprehensive and relatively detailed. I learnt a lot through this course. I highly recommend this course to everyone who wants to learn Recommendation Engine.
Syed
October 11, 2022
Amazing course! The course is understandable and easy to follow. The concepts are very crisp and clear learning content. I learnt a lot and the way it was delivered also very engaging. The lecturer explains on each topic very well and each line of code written. Highly recommended.
Jatin
October 10, 2022
Great course for someone with basic knowledge of machine learning. The course offers a very good combination of theory and practice and good examples of algorithms. It covers the main aspects of the Recommendation Engine in Python. The instructor explains the subject very clearly and also has very good teaching skills. Strongly recommended!!
Arun
July 27, 2022
This is definitely one of the best courses for Recommendation Engine here on Udemy. The content taught is really good and has helped me in understanding recommender systems in an interesting way. The theoretical concepts are clearly explained. Very well structured, easy to follow and informative. I think this course is a good starting point for a beginner. Thank you for the course.
Rida
July 5, 2022
This course is amazing for me. Great contents with theories and code implementation. This course is very useful course, even for beginners. Thank you for your efforts, highly recommended.
Shivam
June 26, 2022
This is very useful course, even for beginners. Thanks to the instructor for efforts. I am excited to take more courses in this area and from the instructor.
Dheeraj
May 22, 2022
When I see the sections of this course there will be 3 projects on recommendation system that's why i bought it, but in this course the instructor mainly focused on the data analysis like in movie recommendation project. The implementation of content and collaborative was nice but in the movie recommendation project I think the instructor should focus on the implementation of different algorithms to improve the recommendations.
RAJ
April 15, 2022
Satisfied with the Content and Explanation... Good Simple Explanation in Layman Terms... Overall Satisfied..!
Anton
December 17, 2021
Narrator speaks clearly & offers good real world cases. Enthusiastic presentations. It would be nice to have more exercise to practice these skills.
Edward
October 19, 2021
I believe the course can be improved by diving more into the concepts and not just reading from the slides. Delivery was very fast which tends to leave a lot of questions behind. Also, please remove the opening and ending clips in each of the video. It's such a waste of time. No need to introduce yourself either.
Edoh
October 10, 2021
I really enjoyed this course because the instructor takes time to explain everything and I learned a lot by taking this course. Thank you for giving me this excellent foundation for the recommendation system.
Israr
October 7, 2021
This course is rich in information, structured in a well form .She makes learning easy for me. Her explanations are clear, she doesn't waste time and goes straight to the point. The course is great I would recommend it
Petronel
October 5, 2021
Great learning course. I wanted to kickstart my Masters in Data Science and this was the perfect place to come to.I enjoyed the course

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4112402
udemy ID
6/9/2021
course created date
6/21/2021
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