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การเข้าถึงหน้านี้ต้องได้รับการอนุญาต คุณสามารถลองเปลี่ยนไดเรกทอรีได้
Notebooks are the primary tool for creating data science and machine learning workflows on Azure Databricks. Databricks notebooks provide real-time coauthoring in multiple languages, automatic versioning, and built-in data visualizations for developing code and presenting results.
Get started with notebooks
Get hands-on experience with step-by-step tutorials that guide you through common use cases.
| Topic | Description |
|---|---|
| Query and visualize data from a notebook | Learn data science basics by using a notebook to query and visualize sample data stored in Unity Catalog using SQL, Python, Scala, and R. |
| Import and visualize CSV data from a notebook | Import data from a CSV file into Unity Catalog, load data into a DataFrame, and visualize data using Python, Scala, and R. |
| EDA techniques using Databricks notebooks | Learn the basics of conducting exploratory data analysis (EDA) using Python in a notebook, from loading data to generating insights. |
| End-to-end classic ML models | Complete tutorial for training classic machine learning models, including data loading, visualization, hyperparameter optimization, and MLflow integration. |
Develop and run notebooks
Learn the fundamentals of creating and using notebooks in your Databricks workspace.
| Topic | Description |
|---|---|
| Basic editing | Learn the basics for how to effectively use and edit notebooks, including cell types, keyboard shortcuts, and essential editing features. |
| Develop code in notebooks | Write and execute code using Python, SQL, Scala, and R with syntax highlighting and IntelliSense. |
| Run notebooks | Execute notebooks and individual cells with flexible compute options and execution controls. |
| Use the Data Science Agent | Custom-built for data science workflows, this Assistant Agent Mode can orchestrate multi-step workflows from a single prompt. Chat with the Data Science Agent to build an entire notebook for tasks like EDA, forecasting, and machine learning from scratch. |
Collaborate and share your work
Work together with your team and share your results effectively.
| Topic | Description |
|---|---|
| Import and export notebooks | Export notebooks in various formats and import notebooks from external sources. |
| Collaborate using notebooks | Share notebooks, use comments, and collaborate in real-time with your team members. |
| Dashboards in notebooks | Build and share interactive dashboards directly from your notebook results. |
Debug and optimize your code
Ensure your notebooks run smoothly and efficiently.
| Topic | Description |
|---|---|
| Code help using Databricks Assistant | Get AI-assisted coding help to debug and write better code faster with intelligent suggestions and explanations. |
| Debug notebooks | Use the interactive debugger to troubleshoot and fix issues in your notebook code. |
| Unit testing | Implement unit testing strategies to validate your notebook code and ensure reliability. |
Popular pages
Explore commonly referenced topics and advanced features for working with notebooks.
| Topic | Description |
|---|---|
| Databricks widgets | Add interactive input parameters to your notebooks and dashboards using widgets. |
| Notebook outputs and results | Manage cell outputs, work with results tables, apply filters, and download data from your notebook results. |
| Orchestrate notebooks and modularize code | Learn techniques for orchestrating notebook workflows and modularizing code. |
| Best practices | Follow recommended practices for efficient and maintainable notebook development. |