Build a Kaggle House‑Price Prediction Pipeline with DataWorks

In today’s data‑driven era, data analysis and machine learning are increasingly important, and house‑price prediction is a classic application both for the real‑estate industry and data‑science enthusiasts. Alibaba Cloud DataWorks provides an all‑in‑one notebook environment to load data, explore, visualize, clean, engineer features, train models, and make regression predictions for Kaggle competitions.

Step 1: Activate DataWorks

Log in to the Alibaba Cloud console with a primary account or a RAM user/role that has AliyunBSSOrderAccess and AliyunDataWorksFullAccess permissions. Open the DataWorks purchase page (https://x.sm.cn/6kP60ji) and configure:

Region – select the target region.

DataWorks version – choose the basic edition.

Purchase duration – 3 months (auto‑renew optional).

Resource group – default name dataworks_default_resource_grc (customizable).

VPC – select the target VPC.

V‑Switch – select the target V‑Switch.

Other settings – keep defaults.

Step 2: Create a DataWorks Workspace

Using the primary account or a RAM user/role with the CreateWorkspace policy, go to the DataWorks console → Workspace list and click “Create Workspace”. Fill in:

Workspace name – custom.

Enable DataStudio (new version) – set to On .

Default resource group – select the resource group created in Step 1.

Other options – keep defaults.

Step 3: Create a Personal Development Environment Instance

Enter the new DataStudio page (https://x.sm.cn/7X1BxKI) and switch the workspace to the one created in Step 2. In the personal development environment dropdown, click “Create New”. Provide:

Instance name – custom.

Resource group – choose the pay‑as‑you‑go DataWorks resource group from Step 1.

Resource quota – e.g., 2CU.

Other settings – keep defaults.

Step 4: Import the Kaggle House‑Price Prediction Notebook

On the DataWorks welcome page, click “DataWorks Gallery” to view notebook cases.

Select the case “Kaggle Competition – House Price Prediction” (https://x.sm.cn/ANC7kdg) and click “Load Case”.

Choose the personal development instance created in Step 3 and confirm.

Follow the notebook’s detailed steps: data loading → data cleaning & preprocessing → feature engineering → model training → model evaluation.

Note: To avoid continuous consumption of the resource‑deduction package, stop the personal development environment when it is not in use via DataStudio → Personal Development Environment → Manage Environment.