ML Learning Series — Mudit Bhalla

A progressive, hands-on collection of machine learning projects documenting my journey from raw data to production-ready models.
Each project tackles a real-world dataset, building on skills introduced in the previous one.

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Project Index

#	Project	Domain	Key Skills	Status
01	Indie Game Sales — Preprocessing Pipeline	Gaming / Market Analysis	Missing value imputation, Label Encoding, StandardScaler	Complete
02	(coming soon)	TBD	TBD	In Progress

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Tech Stack

• Language: Python 3.x
• Environment: Google Colab
• Core Libraries: pandas, numpy, scikit-learn, matplotlib, seaborn

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Series Goals

1. Build a robust preprocessing intuition — imputation strategies, encoding choices, scaling methods
2. Progress to model training — regression, classification, hyperparameter tuning
3. Develop end-to-end ML pipelines deployable in real products

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Repo Structure

ml-learning-series/
├── README.md                    ← You are here
├── project-01-indie-games/
│   ├── README.md
│   ├── notebooks/
│   │   └── indie_games_preprocessing.ipynb
│   ├── data/
│   │   └── README.md            ← Dataset sourcing instructions
│   ├── docs/
│   │   └── pipeline_notes.md
│   └── assets/
│       └── (plots/screenshots)
└── project-02-.../

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By Mudit Bhalla · B.Tech CSE · LinkedIn · GitHub