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Xineoh Media Recommender
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Introduction
How It Works
Prerequisites
Administrator Account and Organisation Creation
Application Creation
Data Set Requirements
Step 1: Data Cleanup
Step 2: Data Transformation
Step 3: Upload to S3 Bucket
Step 4: Sharing S3 Bucket Access to Xineoh’s API
Applications, Datasets and Schemas
Applications
Application Types
Datasets and Schemas
Minimum Requirements for Datasets and Schemas
Customising Datasets and Schemas
Steps in Building a Recommender with the API
Step 1: Batch Upload
Step 2: Build Data and Structures for Training and Testing
Step 3: Train Model
Step 4: Test Model
Step 5: Optimise Meta Parameters
Step 6: User-Clustering - Run Clustering, View Trade-Off, Choose Cluster Count
Step 7: Item-Clustering - Run Clustering, View Trade-Off, Choose Cluster Count
Step 8: Get Recommendations
Sample Implementation - Movielens 25M Dataset
S3 Bucket Creation
Login as Organisation
First Application
Download MovieLens Preprocessed Data
Upload Data to S3 Bucket
Building the Recommender
Uploading S3 Bucket data to Xineoh Platform
Build Data
Train
Test
Optimization
User Clustering and Trade-Off
Item Clustering and Trade-Off
First Recommendations
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Applications, Datasets and Schemas
Applications
Application Types
Datasets and Schemas
Minimum Requirements for Datasets and Schema
Customising Datasets and Schemas
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