Step 4: Sharing S3 Bucket Access to Xineoh’s API

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

Open Navigation

To process the schemas and datasets, Xineoh’s API will need access to your S3 bucket. The security and privacy of your data remain Xineoh’s top priority. To keep your data safe, Xineoh will be keeping your S3 bucket access key and secret key separate.

The first step will be to share your access key with Xineoh via the application management section in the organisations page. Here is where you will manage your applications and their information such as S3 bucket access keys.

The second step will be using your secret key along with your bucket name for the batch processing API call.

Batch Download and Upload


    Url - "{{recommender-api-url}}/builder/batch"
    Request - "POST"
    Params - {
        "version": "v3.0"(Optional)
    }
    Post Data - {
        "aws_secret_key": "YOUR_SECRET_KEY"(Required)
        "aws_bucket": "YOUR_BUCKET_NAME"(Required)
    }

How to use the setup API calls will be explained in greater detail in the step by step section.

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