# jadijadi/machine_learning_with_python_jadi

**Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/jadijadi-machine-learning-with-python-jadi).**

1,127 stars · 397 forks · Jupyter Notebook

## Links

- GitHub: https://github.com/jadijadi/machine_learning_with_python_jadi
- awesome-repositories: https://awesome-repositories.com/repository/jadijadi-machine-learning-with-python-jadi.md

## Description

This repository is a collection of interactive Jupyter notebooks designed as an educational resource for learning machine learning and data science. It provides a structured curriculum that guides users through the development of predictive models and the analysis of datasets using standard Python libraries.

The project utilizes a narrative-driven approach where explanatory text is interleaved with executable code blocks. This format allows learners to execute workflows step-by-step, enabling the visualization of data patterns and the practical implementation of mathematical models within a persistent, local environment.

The materials cover the fundamental principles of machine learning and the application of high-level statistical frameworks. By working through these guided exercises, users can build proficiency in data analysis and the implementation of complex algorithms. The repository is structured as a series of documents that maintain both source code and execution state for reproducibility.

## Tags

### Education & Learning Resources

- [Jupyter Notebook Curricula](https://awesome-repositories.com/f/education-learning-resources/jupyter-notebook-curricula.md) — Serves as a structured learning resource of executable documents for mastering data science and machine learning workflows.
- [Machine Learning Education](https://awesome-repositories.com/f/education-learning-resources/educational-resources/systems-applied-computing/machine-learning-education.md) — Teaches fundamental machine learning principles and practical implementation techniques through guided exercises and educational datasets. ([source](https://github.com/jadijadi/machine_learning_with_python_jadi/blob/main/ML0101EN-Clas-Logistic-Reg-churn.ipynb))
- [Jupyter Notebook Curricula](https://awesome-repositories.com/f/education-learning-resources/jupyter-notebook-curricula/jupyter-notebook-curricula.md) — Delivers a structured machine learning curriculum through interactive Jupyter notebooks that allow step-by-step execution of data science workflows.
- [Data Science Tutorials](https://awesome-repositories.com/f/education-learning-resources/data-science-tutorials.md) — Builds proficiency in data analysis and predictive modeling through structured tutorials and real-world datasets.
- [Interactive Notebooks](https://awesome-repositories.com/f/education-learning-resources/educational-resources/systems-applied-computing/machine-learning-education/interactive-notebooks.md) — Teaches core machine learning principles through a collection of interactive notebooks designed for practical implementation.

### Artificial Intelligence & ML

- [High-Level ML Abstractions](https://awesome-repositories.com/f/artificial-intelligence-ml/high-level-ml-abstractions.md) — Simplifies complex machine learning implementation for students by utilizing high-level statistical and mathematical frameworks.

### Part of an Awesome List

- [Python Data Science Courses](https://awesome-repositories.com/f/awesome-lists/learning/machine-learning-courses/python-data-science-courses.md) — Offers a structured curriculum focused on building predictive models using standard Python data analysis libraries.

### Data & Databases

- [Interactive Data Exploration](https://awesome-repositories.com/f/data-databases/big-data-processing/visual-data-explorers/interactive-data-exploration.md) — Enables interactive exploration of complex algorithms and data patterns by executing code in a notebook environment.