Single Layer Perceptron SLP

Let’s build a Single Layer Perceptron (SLP) with Python

This article aims to explore the world of perceptrons, focusing in particular on the Single Layer Perceptron (SLP), which, although it constitutes only a small fraction of the overall architecture of deep neural networks, provides a solid basis for understanding the fundamental mechanisms of Deep Learning. We will also introduce practical implementation examples in Python, illustrating how to build and visualize an SLP using libraries such as NumPy, NetworkX and Matplotlib.


Logistic Regression with Python

Logistic regression is a type of regression model used for binary classification problems, where the goal is to predict which of two classes an instance belongs to. Unlike linear regression, which predicts continuous values, logistic regression predicts probabilities that vary between 0 and 1. This is achieved by using a logistic (or sigmoid) function to transform the linear output into probabilities.

Machine Learning - The learning Typologies

The learning typologies of Machine Learning

Machine Learning (ML) is a field of artificial intelligence (AI) that focuses on developing algorithms and models that allow computers to learn from data and improve their performance over time without being explicitly programmed. This approach is based on the idea that computers can learn from data, detecting patterns, relationships and regularities, and then apply that knowledge to new data without explicit programming.