Recommendation Algorithms - Advanced Techniques from Billion Dollar Software
Created by Team Mammoth
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Skill level
All levels
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Sections
11
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Lectures
43
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Instructor
Team Mammoth
What's inside
This course includes.
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11
Sections
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43
Lectures
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36
Resources
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Certificate of completion
Included
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Mobile and desktop access
Included
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AI learning assistance
Included
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Course content
Curriculum & lectures.
+ History and Technical Overview 3 lectures
The Big Business of Recommendation Algorithms - A Look at Leading Companies
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The Evolution of Recommendation Systems
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A Technical Overview of Recommendation Algorithms
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+ ▶️ Non-Personalized and Stereotyped Recommender Algorithms 3 lectures
01 Build data to represent course ratings
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02 Analysis of non-personalized recommendations in JS
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01 Source Files
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+ ▶️ Recommend Items with Market Basket Analysis - Data Mining on Purchase Behavior 4 lectures
Market Basket Analysis
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01 Build data for MBA
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02 Calculate support, confidence and lift
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02 Source Files
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+ ▶️ Build Bandit Recommender in JavaScript 5 lectures
01 Build Random Bandit and Arm in JavaScript
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02 Build Runner to simulate Bandit algorithm
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03 Define arms and bandits to test
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04 Calculate precision and recall
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04 Source Files
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+ ▶️ Build a Personalized Item Recommender Algorithm in JavaScript with Pearson Correlation 3 lectures
01 Calculate similarity with Pearson Correlation
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02 Get recommendation
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05 Source Files
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+ Multi-Armed Bandit Algorithms as Recommenders 1 lecture
Multi-Armed Bandit Algorithms as Recommenders
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+ ▶️ Coverage, Novelty, Diversity and Serendipity of Recommenders 7 lectures
Coverage, Novelty, Diversity and Serendipity
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01 Build user data in JavaScript
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02 Calculate Coverage Metric of Algorithm Recommendations
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03 Calculate Novelty Metric of Algorithm Recommendations
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04 Calculate Diversity Metric of Algorithm Recommendations
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05 Calculate Serendipity Metric of Algorithm Recommendations
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06 Source Files
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+ ▶️ Recommender Algorithm Example in Godot with C# 3 lectures
01 Build user data in Godot with C#
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02 Collaborative filtering in Godot with C#
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07 Source files
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+ ▶️ Build Content-Based Filtering in Godot with Csharp 2 lectures
04 Build content-based filtering in Godot with Csharp
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08 Resources
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+ ▶️ Build Alternating Least Squares Recommender in Godot with Csharp 4 lectures
01 Build an Interaction Matrix
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02 Build Alternating Least Squares Recommender Algorithm
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03 Recommend Items for a User
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09 Source Files
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+ ▶️ Evaluation Metrics for Recommender Systems 8 lectures
Evaluation Metrics for Recommender Systems
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01 Calculate Precision in Godot Csharp
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02 Calculate Recall in Godot Csharp
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03 Calculate F1-Score in Godot Csharp
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04 Calculate Mean Absolute Error in Godot Csharp
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05 Calculate Root Mean Square Error in Godot Csharp
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06 Calculate ROC-AUC in Godot Csharp
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10 Source Files
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Instructors
Taught by people who ship.
Team Mammoth
Instructor
Produced by a team of Mammoth Club industry experts. Over 14 years, Mammoth Club has built a global student community in 190+ countries with 9+ million courses sold, releasing over 1,000+ courses and 5,000+ hours of video content.
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