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ML-For-Beginners
Knowledge Tutorial

This project is an educational resource for learning Machine Learning, specifically focusing on Natural Language Processing (NLP). It features a Romanian translation of a lesson that teaches how to perform Sentiment Analysis on hotel reviews using the NLTK library and the VADER scoring tool.

18
Chapters
-
Subsystems
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.

👥
AGENTS.md
AGENTS.md
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translations/ro/6-NLP/5-Hotel-Reviews-2/notebook.ipynb
translations/ro/6-NLP/5-Hotel-Reviews-2/notebook.ipynb
⚙️
CODE_OF_CONDUCT.md
CODE_OF_CONDUCT.md
⚙️
1-Introduction
1-Introduction
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notebook.ipynb
notebook.ipynb
⚙️
sketchnotes
sketchnotes
⚙️
quiz-app
quiz-app
⚙️
2-Regression
2-Regression
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3-Web-App
3-Web-App
⚙️
4-Classification
4-Classification
⚙️
5-Clustering
5-Clustering
⚙️
6-NLP
6-NLP
ML-For-Beginners — bash
open tutorial
◆ Scanning numbered chapters
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Repository Overview

Intro and Architecture Diagram

This project is an educational resource for learning Machine Learning, specifically focusing on Natural Language Processing (NLP). It features a Romanian translation of a lesson that teaches how to perform Sentiment Analysis on hotel reviews using the NLTK library and the VADER scoring tool.

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

flowchart TD A0["translations/ro/6-NLP/5-Hotel-Reviews-2/notebook.ipynb"] A0 -->|"Executes analysis workflow"| A0
Tutorial Chapters

All 18 chapters

Follow sequentially or jump to any topic. Start with AGENTS.md.

Ch.01 AGENTS
AGENTS.md
Welcome to ML-For-Beginners! This is the very first chapter of our journey. Before we dive into Python code, regressions, or neural network…
Ch.01 TOOLS
translations/ro/6-NLP/5-Hotel-Reviews-2/notebook.ipynb
Welcome to the first chapter of your journey into Natural Language Processing (NLP)!
Ch.02 CORE
CODE_OF_CONDUCT.md
Welcome to the second chapter! In the previous chapter, AGENTS.md, we learned how to teach AI robots to understand our project.
Ch.03 CORE
1-Introduction
Welcome to the third chapter! In the previous chapter, CODE_OF_CONDUCT.md, we established the rules for how humans should behave in this co…
Ch.04 TOOLS
notebook.ipynb
Welcome to the fourth chapter! In the previous chapter, 1-Introduction, we learned the history, definitions, and fairness concepts of Machi…
Ch.05 CORE
sketchnotes
Welcome to the fifth chapter! In the previous chapter, notebook.ipynb, we learned how to use Jupyter Notebooks as our digital lab journal f…
Ch.06 CORE
quiz-app
Welcome to the sixth chapter! In the previous chapter, sketchnotes, we explored how to use visual drawings to understand complex concepts.…
Ch.07 CORE
2-Regression
Welcome to Chapter 7! In the previous chapter, quiz-app, we built a tool to test our knowledge. We ensured our brains were ready.
Ch.08 CORE
3-Web-App
Welcome to Chapter 8! In the previous chapter, 2-Regression, we successfully built a Machine Learning model. We taught a computer how to pr…
Ch.09 CORE
4-Classification
Welcome to Chapter 9! In the previous chapter, 3-Web-App, we took our regression model and put it on the web. We learned to predict numbers…
Ch.10 CORE
5-Clustering
Welcome to Chapter 10! In the previous chapter, 4-Classification, we taught a robot how to sort data into specific buckets (like "Cat" or "…
Ch.11 CORE
6-NLP
Welcome to Chapter 11! In the previous chapter, 5-Clustering, we learned how to group similar data points together even if we didn't know w…
Ch.12 CORE
7-TimeSeries
Welcome to Chapter 12! In the previous chapter, 6-NLP, we learned how to teach computers to read and understand human language. We dealt wi…
Ch.13 CORE
8-Reinforcement
Welcome to Chapter 13! In the previous chapter, 7-TimeSeries, we learned how to predict the future by analyzing the history of the past. We…
Ch.14 CORE
9-Real-World
Welcome to Chapter 14! In the previous chapter, 8-Reinforcement, we reached the cutting edge of AI, teaching computers to learn by trial an…
Ch.15 CORE
solution/R/
Welcome to Chapter 15! In the previous chapter, 9-Real-World, we finished our journey through the core Machine Learning curriculum. We lear…
Ch.16 CORE
translations
Welcome to Chapter 16! In the previous chapter, solution/R/, we learned that Data Science can be done in different programming languages, l…
Ch.17 TOOLS
.github/workflows/co-op-translator.yml
Welcome to the final chapter! In the previous chapter, translations, we explored the massive directory that holds this course in over 40 di…
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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