Teroaz / learning-scikit-learn

Personal notes from the "Hands-on Machine Learning with Scikit-Learn" educative.io course

📝 Notes : Hands-on Machine Learning with Scikit-Learn

Introduction

This repository contains my personal notes and Jupyter notebooks for the machine learning course provided by educative.io. It serves as both a revision toolkit for school modules and a reference guide for machine learning concepts implemented using scikit-learn.

Installation and Setup

Before running the notebook, ensure that you have the following installed:

• Python 3.x
• Jupyter Notebook or JupyterLab
• scikit-learn

You can install the necessary libraries using pip:

pip install notebook scikit-learn matplotlib seaborn pandas numpy

Directory Structure

The project is structured into different folders, each representing a module of the course:

• Working with Datasets
  • Loading and visualizing built-in datasets
  • Generating synthetic datasets for practice
  • Preprocessing data for machine learning tasks
• Feature Engineering
  • Techniques for feature selection
  • Methods for feature extraction
  • Handling missing values in datasets
• LinearRegression.ipynb

Concepts Covered

The key machine learning concepts covered in this repository include:

• Working with datasets (loading, visualizing, and preprocessing)
• Feature engineering (feature selection, extraction, and handling missing values)
• Linear regression and its implementation using scikit-learn

Notebooks and Notes Usage

To view and interact with the notebooks, navigate to the respective folder and open the notebook file (.ipynb) using Jupyter Notebook or JupyterLab. The markdown files (.md) contain concise notes on the topic covered.

Resources

• Course Link: Hands-on Machine Learning with scikit-learn
• scikit-learn Documentation: scikit-learn.org

To-Do

• Add more notebooks and notes for other modules
• Include more examples and exercises for each concept

BTW : I've been postponing the completion of this project as its primary purpose was to serve as a revision aid for a particular school module, which diminished my motivation to finalize it post-course.