Building real world books recommendation engine with Python
Building real world books recommendation engine with Python, available at $19.99, has an average rating of 3.75, with 12 lectures, based on 27 reviews, and has 99 subscribers.
You will learn about 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 This course is ideal for individuals who are Beginner python developer who are curious to learn about how to apply collaborative filtering to solve real world problems. It is particularly useful for Beginner python developer who are curious to learn about how to apply collaborative filtering to solve real world problems.
Enroll now: Building real world books recommendation engine with Python
Summary
Title: Building real world books recommendation engine with Python
Price: $19.99
Average Rating: 3.75
Number of Lectures: 12
Number of Published Lectures: 12
Number of Curriculum Items: 12
Number of Published Curriculum Objects: 12
Original Price: $22.99
Quality Status: approved
Status: Live
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
Who Should Attend
- Beginner python developer who are curious to learn about how to apply collaborative filtering to solve real world problems.
Target Audiences
- Beginner python developer who are curious to learn about how to apply collaborative filtering to solve real world problems.
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.
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Understanding of recommendation systems
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Leverage Collaborative filtering to classify documents
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User Jupyter Notebook for programming
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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?
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Learn recommendations systems and build real world books recommendation engine from professional trainer from your own desk.
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Over 10 lectures teaching you how to build real world recommendation systems
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Suitable for beginner programmers and ideal for users who learn faster when shown.
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Visual training method, offering users increased retention and accelerated learning.
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Breaks even the most complex applications down into simplistic steps.
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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.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: Course Outline
Lecture 3: What are recommendation systems?
Lecture 4: About Author
Chapter 2: Set Up
Lecture 1: Install Python
Lecture 2: Install Anaconda
Chapter 3: Experimentation
Lecture 1: Getting Books Data
Lecture 2: Cross Tab
Lecture 3: Understanding SVD
Lecture 4: Recommending similar books
Chapter 4: Web Application
Lecture 1: Buidling WebApp
Lecture 2: Next Steps
Instructors
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Evergreen Technologies
Software Mentor
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 2 votes
- 3 stars: 6 votes
- 4 stars: 7 votes
- 5 stars: 11 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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