Recommendation Algorithms - Advanced Techniques from Billion Dollar Software

Master the sophisticated methodologies and advanced techniques underpinning modern recommendation systems, used by some of the world's most lucrative tech companies.

Develop amazing demos to harness your knowledge in a hands-on manner in GODOT through C# code.

Participants will explore the intricacies of algorithms that drive personalized content and product suggestions, including collaborative filtering, content-based filtering, matrix factorization, and deep learning approaches.


 

The course combines theoretical insights with practical, hands-on applications, equipping learners with the skills to implement these technologies in real-world scenarios.

A unique feature of this offering is its exclusive availability through Humble Bundle for the first time, providing unprecedented access to cutting-edge knowledge and industry practices.

Ideal for data scientists, engineers, and tech enthusiasts, this course aims to elevate your proficiency in building scalable and efficient recommendation engines that can significantly enhance user experience and engagement.

Your Instructor


Alexandra Kropf
Alexandra Kropf

Alexandra Kropf is Mammoth Interactive's CLO and a software developer with extensive experience in full-stack web development, app development and game development. She has helped produce courses for Mammoth Interactive since 2016, including the Coding Interview series in Java, JavaScript, C++, C#, Python and Swift.

Mammoth Interactive is a leading online course provider in everything from learning to code to becoming a YouTube star. Mammoth Interactive courses have been featured on Harvard’s edX, Business Insider and more.

Over 12 years, Mammoth Interactive has built a global student community with 4 million courses sold. Mammoth Interactive has released over 350 courses and 3,500 hours of video content.

Founder and CEO John Bura has been programming since 1997 and teaching since 2002. John has created top-selling applications for iOS, Xbox and more. John also runs SaaS company Devonian Apps, building efficiency-minded software for technology workers like you.


Course Curriculum


  Welcome
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  Non-Personalized and Stereotyped Recommender Algorithms
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  Recommend Items with Market Basket Analysis - Data Mining on Purchase Behavior
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  Multi-Armed Bandit Algorithms as Recommenders
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  Build Bandit Recommender in JavaScript
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  Build a Personalized Item Recommender Algorithm in JavaScript with Pearson Correlation
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  Coverage, Novelty, Diversity and Serendipity of Recommenders
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  Recommender Algorithm Example in Godot with C#
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  Build Content-Based Filtering in Godot with Csharp
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  Build Alternating Least Squares Recommender in Godot with Csharp
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  Evaluation Metrics for Recommender Systems
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Frequently Asked Questions


When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish.
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
What if I am unhappy with the course?
We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.

Get started now!