Machine Learning Classes

Welcome to Tiago Cabo's Machine Learning Classes repository! This repository contains structured learning materials for data science and machine learning, covering foundational concepts, core machine learning techniques, and deep learning models.

📂 Directory Structure

└── tiagocabo-machine-learning-classes/
    ├── README.md  # This file
    ├── LICENSE  # License information
    ├── Pipfile  # Dependencies and package management
    ├── 0-introduction-to-data-science/  # Introductory content
    ├── 1-python/  # Python programming fundamentals
    ├── 2-core-machine-learning/  # Core machine learning concepts
    └── 3-deep-learning/  # Deep learning and advanced topics

📖 Contents Overview

0. Introduction to Data Science

Introduction to the field of data science, its applications, and fundamental concepts.

1. Python Fundamentals (Link)

Contains Jupyter notebooks and markdown files covering:

• Python basics (1.python.ipynb)
• Data manipulation with Pandas (2.Pandas.ipynb)
• Numerical computing with NumPy (3.Numpy.ipynb)
• Data visualization with Matplotlib & Seaborn (4.Matplotlib_Seaborn.ipynb)
• SOLID principles (5.SOLID_principles.md)
• Data structures (6.Data_structure.md)
• Design patterns (design_patterns/)
• Exercises (exercises/)

2. Core Machine Learning (Link)

• Statistics (1-statistics/)
• Supervised Learning (Intro & Advanced) (2-supervised-learning-intro/, 3-supervised-learning-advanced/)
• Regression & Unsupervised Learning (4-regression_and_unsupervised_learning/)
• Anomaly Detection, Time Series & Recommenders (5-anomaly-detection-time-series-recommenders/)

3. Deep Learning (Link)

• Deep Neural Networks (DNNs) (1-deep-neural-networks/)
• Convolutional Neural Networks (CNNs) (2-CNNs/)
• Recurrent Neural Networks (RNNs) & NLP (3-RNNs/)

🔧 Getting Started

Installation

To set up the environment, install dependencies using pipenv:

pip install pipenv  # Install pipenv if not already installed
pipenv install  # Install dependencies
pipenv shell  # Activate virtual environment

Running Jupyter Notebooks

Launch Jupyter Notebook to interact with the materials:

jupyter notebook

Dataset Usage

Several datasets such as Titanic, Credit Card Fraud, Housing Prices, and Twitter Sentiment are included in their respective sections.

📜 License

This project is licensed under the MIT License. See LICENSE for details.

📬 Contributions & Feedback

Feel free to open issues or submit pull requests if you'd like to contribute. Feedback is always welcome!

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Happy Learning! 🚀