Deep Learning (2023) - UNLP

This repository contains the practices and exercises completed as part of the "Deep Learning" course at the Universidad Nacional de La Plata (UNLP) in 2023.

Content

• Practice 1: Introduction to Pandas and NumPy

• Practice 2: Perceptron
  Implementation of the Perceptron algorithm, exploring the basics of binary classification.

• Practice 3: Linear Combinator, Non-linear Neuron, and Gradient Descent
  Concepts of linear and non-linear neurons, stochastic gradient descent, linear regression, and logistic regression.

• Practice 4: Multi-Layer Perceptron and Keras with MNIST
  Building a simple Multi-Layer Perceptron (MLP) using Keras, with applications on the MNIST dataset.

• Practice 5: Convolutional Neural Networks (CNNs)
  Introduction to Convolutional Neural Networks, focusing on their architecture and implementation.