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ML-For-Beginners
Knowledge Tutorial

This project is a comprehensive 12-week curriculum designed to introduce Machine Learning concepts to beginners. It features a mix of written lessons, code demonstrations in Python and R, and an interactive Vue.js quiz application to reinforce learning across 26 distinct lessons.

15

Chapters

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Subsystems

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Rabbit Holes

▶ Start Reading ⎇ View on GitHub

System Architecture

How the pieces fit

ML-For-Beginners is organized as connected concepts and components. Start broad, then drill down chapter by chapter.

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Project Overview

Project Overview

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Key Technologies

Key Technologies

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Repository Structure

Repository Structure

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Lesson Structure

Lesson Structure

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Python Setup

Python Setup

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R Setup

R Setup

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Quiz Application Development

Quiz Application Development

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Development Workflow

Development Workflow

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Contribution Guidelines

Contribution Guidelines

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Code Style Guidelines

Code Style Guidelines

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Troubleshooting

Troubleshooting

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Testing and Validation

Testing and Validation

ML-For-Beginners — bash

➜open tutorial

◆ Scanning numbered chapters

◆ Building navigation and Mermaid diagrams

◆ Generating chapter and subsystem pages

✓ 15 chapter pages built

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Repository Overview

Intro and Architecture Diagram

This project is a comprehensive 12-week curriculum designed to introduce Machine Learning concepts to beginners. It features a mix of written lessons, code demonstrations in Python and R, and an interactive Vue.js quiz application to reinforce learning across 26 distinct lessons.

Source Repository: https://github.com/microsoft/ML-For-Beginners

flowchart TD A0["Project Overview"] A1["Repository Structure"] A2["Python Setup"] A3["R Setup"] A4["Quiz Application Development"] A5["Documentation Setup"] A6["Development Workflow"] A7["Testing and Validation"] A8["Code Style Guidelines"] A9["Deployment"] A10["Translation Workflow"] A11["Contribution Guidelines"] A12["Lesson Structure"] A13["Troubleshooting"] A14["Key Technologies"] A1 -->|"Organizes files"| A0 A12 -->|"Structures content"| A0 A14 -->|"Underlies"| A2 A14 -->|"Underlies"| A3 A14 -->|"Underlies"| A4 A6 -->|"Uses environment"| A2 A6 -->|"Uses environment"| A3 A4 -->|"Enhances interactivity"| A12 A7 -->|"Validates"| A4 A9 -->|"Publishes"| A4 A5 -->|"Generates guides"| A0 A10 -->|"Localizes"| A0 A11 -->|"Modifies"| A1 A8 -->|"Governs"| A11 A13 -->|"Unblocks"| A6

Tutorial Chapters

All 15 chapters

Follow sequentially or jump to any topic. Start with Project Overview.

Project Overview

Welcome to the start of your journey! If you are reading this, you are likely interested in Machine Learning (ML) but might be feeling a li…

Key Technologies

In the previous chapter, Project Overview, we introduced ML-For-Beginners as a "Cookbook" for learning Machine Learning.

Repository Structure

In the previous chapter, Key Technologies, we gathered our tools—Python, R, Visual Studio Code, and Git. Now that we have our equipment, we…

Lesson Structure

In the previous chapter, Repository Structure, we learned how to navigate the "Library" of folders to find the topic we want.

In the previous chapter, Lesson Structure, we opened the "Cookbook" and looked at how a lesson is organized. We saw that the core of the le…

In the previous chapter, Python Setup, we set up a "kitchen" for cooking data using Python.

Quiz Application Development

In the previous chapters, Python Setup and R Setup, we set up the environment to run the data science code.

Development Workflow

In the previous chapter, Quiz Application Development, we explored the engine behind the interactive quizzes. Before that, in Python Setup…

Contribution Guidelines

In the previous chapter, Development Workflow, we learned how to fix a bug or add a feature on your own computer. We created a "Branch" (a…

Code Style Guidelines

In the previous chapter, Contribution Guidelines, we learned how to submit a "Pull Request" to share your work with the community.

Troubleshooting

In the previous chapter, Code Style Guidelines, we learned how to write code that looks good and follows the rules.

Testing and Validation

In the previous chapter, Troubleshooting, we learned how to fix things when they break. We acted like detectives, reading error messages to…

Translation Workflow

In the previous chapter, Testing and Validation, we ensured our code works correctly by running automated tests and linters.

Documentation Setup

In the previous chapter, Translation Workflow, we learned how to translate our lessons into many different languages using robots and human…

In the previous chapter, Documentation Setup, we learned how to turn our Markdown files into a beautiful website. We used docsify serve to…

About This Project

Generated by Code IQ

This tutorial was automatically generated by Code IQ and rendered with the shared tutorial site builder. It can be produced for any repository tutorial folder that follows the numbered markdown chapter layout.

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// → 15 chapters
// → source: microsoft/ML-For-Beginners