Artificial Neural Networks and Deep Learning - Portfolio

Author: Felipe Maluli de Carvalho Dias
Course: Artificial Neural Networks and Deep Learning
Institution: Insper
Edition: 2025.2

Project Structure

• Data Exercise - Data preparation and analysis
• Perceptron Exercise - Single-layer perceptron implementation
• MLP Exercise - Multi-layer perceptron implementation
• Metrics Exercise - Machine learning evaluation metrics

Entregas

• Data Exercise - Data Preparation and Analysis
• Perceptron Exercise - Single-Layer Perceptron Implementation
• MLP Exercise - Multi-Layer Perceptron Implementation
• VAE Exercise - Variational Autoencoder Implementation

Installation and Setup

To run the exercises in this repository, follow these steps:

1. Clone the repository:

   git clone https://github.com/FeMCDias/Artificial-Neural-Networks-and-Deep-Learning.git
   cd Artificial-Neural-Networks-and-Deep-Learning
   

2. Create and activate a virtual environment:

   python3 -m venv env
   source env/bin/activate  # On Windows: env\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. View the documentation:

   mkdocs serve
   

5. Deploy to GitHub Pages:

   mkdocs gh-deploy
   

References

• Neural Networks and Deep Learning - Michael Nielsen
• Deep Learning Book - Ian Goodfellow