> ## Documentation Index
> Fetch the complete documentation index at: https://docs.clickml.app/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction to ClickML Studio

> ClickML Studio is a no-code visual platform for building, training, and evaluating machine learning pipelines through drag-and-drop components.

## What is ClickML Studio?

ClickML Studio is a **no-code machine learning platform** that lets you build, train, and evaluate ML pipelines visually — no programming required.

You work on a canvas where you drag components onto the screen, connect them together, and run the pipeline. Each component performs one specific task: reading data, cleaning it, training a model, evaluating results.

## How it works

<Steps>
  <Step title="Create a project">
    Start a new project and give it a name and problem type (classification or regression).
  </Step>

  <Step title="Build your pipeline on the canvas">
    Drag components from the toolbox onto the canvas. Connect them by drawing edges from one component's output to the next component's input.
  </Step>

  <Step title="Configure each component">
    Click a component to open its inspector panel on the right. Fill in the settings (upload a file, choose a strategy, pick a model).
  </Step>

  <Step title="Run the pipeline">
    Hit Run. The pipeline executes from left to right. Each component passes its output to the next.
  </Step>

  <Step title="Review results">
    Open the Evaluation component to see metrics, charts, and model performance.
  </Step>
</Steps>

## Component categories

| Category                   | What it does                                  |
| -------------------------- | --------------------------------------------- |
| **Data**                   | Load data from a file or URL                  |
| **Data Processing**        | Clean, scale, encode, and split your data     |
| **Feature Engineering**    | Create, transform, and select features        |
| **Data Wrangling**         | Merge or concatenate multiple datasets        |
| **Analytics**              | Explore your data with EDA                    |
| **Models**                 | Train classification or regression models     |
| **Evaluation & Inference** | Measure model performance and run predictions |