Pinned Loading

1. setu-compliance-rag setu-compliance-rag Public

   SETU Compliance multi-agent RAG chatbot over 48 policy PDFs

   Python 1 1

2. Product Recommendations Product Recommendations

   1

   {

   2

       "nbformat_minor": 1, 

   3

       "cells": [

   4

           {

   5

               "source": "# Build a product recommendation engine\n\nIn this notebook, you will:\n\n* load historical shopping data\n* structure and view that data in a table that displays customer information, product categories, and shopping history details\n* use the *k*-means algorithm, which is useful for cluster analysis in data mining, to segment customers into clusters for the purpose of making an in-store purchase recommendation based on shopping history\n* deploy the model to the IBM Watson Machine Learning service in IBM Cloud to create your recommendation application \n\nBy the end of the notebook, you will understand how to build a model to provide product recommendations for customers based on their purchase history.\n\nThis notebook runs on Python 3.x with Apache Spark 2.1.\n\n## Table of contents\n\n1. [Setup](#setup)<br>\n    1.1. [Import libraries](#libraries)<br>\n    1.2. [Setup WML Credentials](#cred)<br>\n    1.3. [Load sample data](#load)<br>\n    1.4. [View data in a table](#view_table)<br>\n2. [Create a KMeans model](#kmeans)<br>\n    2.1. [Prepare data](#prepare_data)<br>\n    2.2. [Create clusters and define the model](#build_model)<br>\n3. [Persist the model](#persist)<br>\t\n4. [Deploy the model to the cloud](#deploy)<br>\n\t4.1. [Create deployment for the model](#create_deploy)<br>\n\t4.2. [Test model deployment](#test_deploy)<br>\n5. [Create product recommendations](#create_recomm)<br>\n\t5.1. [Test product recommendations model](#test_recomm)<br>\n6. [Summary and next steps](#summary)<br>\n\n<a id=\"setup\"></a>\n## 1. Setup\n\nInstall and import the required libraries and load the customer shopping data into this notebook.\n\n[PixieDust](https://pixiedust.github.io/pixiedust/) is a Python helper library. We are using it in this notebook to load and visualize data.", 

3. Blockchain_AircraftLeasing Blockchain_AircraftLeasing Public

   Aircraft Leasing

4. Certfications Certfications Public

5. docker-node docker-node Public

   Forked from nodejs/docker-node

   Official Docker Image for Node.js 🐳 🐢 🚀

   Shell

6. global-financing-blockchain global-financing-blockchain Public

   Forked from IBM/global-financing-blockchain

   JavaScript