🧠 Machine Learning Research Roadmap

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🎯 Why This Repository Exists

Most Machine Learning resources teach you how to train models.

Few teach you how to think like a researcher.

This repository documents my journey of learning Machine Learning Research from the ground up, covering everything from research fundamentals and experimental design to reproducible studies and real-world research projects.

The goal is not just to build models.

The goal is to understand why models work, when they fail, and how they can be improved.

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🔬 What is Machine Learning Research?

Machine Learning Research is the process of generating new knowledge through systematic experimentation.

Instead of asking:

Can I build a model?

Researchers ask:

Can I better understand, improve, or extend existing methods?

Research combines curiosity, experimentation, and evidence-based conclusions.

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🗺️ Research Workflow

💡 Idea
   ↓
❓ Research Question
   ↓
📝 Hypothesis
   ↓
📊 Dataset
   ↓
⚙️ Experiment
   ↓
📈 Evaluation
   ↓
🔍 Insight
   ↓
🚀 Contribution

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📚 Roadmap

Phase 1 — Research Foundations

• What is Machine Learning Research?
• Research Workflow
• Research Question Formulation
• Hypothesis Creation
• Literature Review
• Reading Research Papers
• Identifying Research Gaps

Phase 2 — Experimental Design

• Dataset Selection
• Baseline Models
• Experimental Methodology
• Reproducibility
• Evaluation Metrics
• Cross Validation
• Statistical Testing

Phase 3 — Applied Machine Learning Research

• Tabular Data Research
• Feature Engineering Studies
• NLP Research
• Computer Vision Research
• Explainable AI
• Deep Learning Experiments

Phase 4 — Capstone Research Project

An end-to-end machine learning research study including:

• Problem Formulation
• Literature Review
• Methodology
• Experiments
• Statistical Validation
• Discussion
• Future Work

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📂 Repository Structure

machine-learning-research-roadmap/
│
├── README.md
│
├── Day-01-What-Is-ML-Research/
├── Day-02-Research-Workflow/
├── Day-03-Research-Questions/
│── .....
├── Research-Projects/
│
└── assets/

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🎓 Learning Outcomes

By completing this roadmap, I aim to develop the ability to:

• Formulate research questions
• Design reproducible experiments
• Compare machine learning methodologies
• Interpret results scientifically
• Conduct independent research studies
• Build a public research portfolio

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🚀 Start Here

Day 1 — What is Machine Learning Research?

The first chapter introduces the mindset shift from building machine learning projects to conducting machine learning research. https://github.com/Yashashree-Joshi/machine-learning-research-roadmap/tree/main/Day-01-What-Is-ML-Research