Amazon Product Recommendation System AI
Amazon Product Recommendation System Recommendation Systems Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. Contents / Agenda ● Business Problem Overview and Solution Approach ● EDA Results ● Rank-Based Recommendation System ● User-User Similarity-Based Recommendation System ● Item-Item Similarity-Based Recommendation System ● Model-Based Recommendation System ● Model Performance Comparison ● Appendix Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. Data Definition ● In this project, we will be using the Amazon dataset, which contains the following attributes: ○ userId: Every user identified with a unique id ○ productId: Every product identified with a unique id ○ Rating: The rating of the corresponding product by the corresponding user Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. How to use this deck? ● This slide deck serves as a comprehensive template for your project submission ● Within this deck, you will come across various questions that are intended to test your ability to understand data visualizations, discover patterns / insights and postulate hypothesis. Think thoroughly and provide answers to these questions ● You are encouraged to modify this deck as required, by replacing the questions with suitable answers ● Please feel free to incorporate additional points if you deem necessary Note: The data visualizations you see in this deck are obtained from RapidMiner Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. Business Problem Overview and Solution Approach ● Please define the problem ● Please mention the solution approach / methodology Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. Exploratory Data Analysis Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. EDA Results – Summary Statistics ● What is the average rating of products? ● Are there missing values in the data? Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. EDA Results – Unique users and products ● What is the number of unique users and unique products in the dataset? What is the possible number of interactions between users and products? Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. EDA Results – Ratings Distribution ● What is the most common rating given by users? What is the range of ratings given by users? ● Are the ratings skewed towards higher or lower values? Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. Model Building Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. Rank-Based Recommendation System ● Please comment on the output shown in the table ● What is the advantage and disadvantage of using Rank-based Recommendation Systems? Note: The table shows the prediction from the RankBased Recommendation System. Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. User-User Similarity-Based Recommendation System ● Please comment on model performance Note: The below tables, respectively, shows the performance of the model and the sample recommendation for a user with the actual rating and the predicted rating. Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. Item-Item Similarity-Based Recommendation System ● Please comment on model performance Note: The below tables, respectively, shows the performance of the model and the sample recommendation for a user with the actual rating and the predicted rating. Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. Model-Based Recommendation System ● Please comment on model performance Note: The below tables, respectively, shows the performance of the model and the sample recommendation for a user with the actual rating and the predicted rating. Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. Model Performance Comparison ● Please provide observations on comparison of different models. Which model should be chosen to solve the problem? And why? Note: The below table shows the performance metrics of all the collaborative filtering based models applied in this project. Model Name/Performance Metrics RMSE MAE NMAE Item-Item Collaborative 1.175 0.899 0.225 User-User Collaborative 1.202 0.912 0.228 Model-based Collaborative (SVD) 1.214 0.977 0.244 Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. APPENDIX Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. Data Background and Contents ● Please mention the data background and contents Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. Slide Header ● Please add any other pointers (if needed) Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. Happy Learning ! Proprietary content. © Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. 19
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