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🧭
Here will stand all my stuff for the participation to ML Zoomcamp 2025.
You will find My notes, resources, repos, projects, articles
I hope you will find interesting things for you.
You can suggest all what you think that could be useful for others in comments.
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Official Course resources
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Repository:
https://github.com/DataTalksClub/machine-learning-zoomcamp
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Playlist:
Machine Learning Zoomcamp
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1) Introduction to ML
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📚
- Intro to ML
- ML vs Rule-based Systems
- Supervised ML
- CRISP-DM Method
- Model Selection process
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📚
- Environment set up/ Github Codespaces
- Intro to Numpy
- Linear Algebra Refresher
- Intro to Pandas
- Summary
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Personal work:
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💡
Personal notes from chapter 1
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📚
https://github.com/DataScienceMyLove/homeworks-ml-zoomcamp-2025/blob/main/01-intro/homework-1.ipynb
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Sources:
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📚
2) Regression
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📚
- Car Price prediction project
- Data Preparation
- Exploratory Data Analysis
- Setting Up the validation framework
- Linear Regression
- Linear Regression: Vector form
- Traing Linear Regression: Normal Equation
- Baseline Model for Car Price Prediction Project
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📚
- Root Mean Squared Error
- Computing RMSE on Validation Data
- Feature Engineering
- Categorical Variables
- Regularization
- Fine-tune the model
- Using the model
- Summary of the chapter
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Personal work:
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Personal notes from chapter 2: Car price prediction project
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📚
Homework 2: Key concepts/ideas to keep in mind 🧑🏭
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📚
https://github.com/DataScienceMyLove/homeworks-ml-zoomcamp-2025/blob/main/02-linear_regression/homework-2.ipynb
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📚
https://github.com/DataScienceMyLove/Car-price-prediction/blob/main/car-price-prediction-project.ipynb
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Useful Resources for this chapter
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