---
title: "Prerequisites"
url: https://docs.catalyst.zoho.com/en/tutorials/movie-recommendation/prerequisites/
description: "Create a powerful ML pipeline that analyzed historic Movie data and gives meaningful recommendation using the Catalyst QuickML components."
last_updated: 2026-02-24T17:50:04Z
service: All Services
type: tutorial
related_links:
  - name: "Machine Learning Algorithms"
    url: /en/quickml/help/ml-algorithms/classification-algorithms/
---

# Prerequisites

Since this tutorial is focused solely on Catalyst QuickML, all tasks—including building data and ML pipelines, creating models, and training them for recommendations—will be performed within the [Catalyst console](https://console.catalyst.zoho.com/).

Before getting started, download the following datasets:
* [Item_features_dataset.csv](https://workdrive.zohoexternal.com/external/9fd00bbcd32180b5dcc4c053314a424e8fff6c417dbe55004dc1908f78b7a58f): Contains movie-related details, such as titles, release dates, and genres
* [Interaction_dataset.csv](https://workdrive.zohoexternal.com/external/d7cdd2670e6717d9e086769e897988af5f7ae2009cdc6b6cd263cb863c991428): Contains movie rating details
* [User_features_dataset.csv](https://workdrive.zohoexternal.com/external/ed8754d1345b3814062040bc80dcacc5e7587b3332284a26feb97df5983d2a4c): Contains user information such as user ID, age, gender, and occupation

This tutorial will guide you through cleaning, refining, and preprocessing these datasets, which will then be used for training the recommendation model.