Perceptrón Paso a Paso con Python: La Base de las Redes Neuronales Artificiales de Machine Learning

Step-by-step explanation of the creation and training of the Perceptron: one of the first artificial neurons. The Perceptron is programmed using Python. 👉 Xiperia offers business consulting that transforms data into actionable knowledge to achieve your business objectives. Learn more at https://www.xiperia.com ℹ️ Octavio Gutiérrez is solely responsible for the content, statements, and opinions expressed in this video, which are not affiliated with the organizations he is associated with. 🌐 To learn more about Octavio Gutiérrez, visit his LinkedIn profile:   / octaviogutierrez   To cite this educational resource, use the following reference: Gutiérrez-García, J.O. [Machine Code]. (2022, January 17). Perceptron Step by Step with Python: The Basis of Artificial Neural Networks for Machine Learning [Video]. YouTube. [Include the video URL here]. **************************************** To guide your learning, this link (   • Curso de Inteligencia Artificial (IA) y Ma...  ) contains a sequential guide to learning: 1. Basic Programming with Python; 2. Data Handling; 3. Data Visualization; 4. Data Analysis; and 5. Machine Learning and Data Science. *********************************************** Video Index: 0:00 Introduction 0:36 Biological Neurons 3:07 Perceptron Structure 5:53 Training Data 12:27 Activation Function (Step) 24:08 Perceptron Training 37:58 Visualization of the Areas Corresponding to Each Class 39:30 Perceptron with Scikit-learn / Sklearn ⭐ Support Código Máquina by liking, commenting, sharing, or saying a big thank you. 📊 The data doesn't lie: Hair loss is slowed down with predictive, not corrective, maintenance. The new solid anti-hair loss shampoo from the co-founder of Código Máquina is the high-performance upgrade your biological hardware needs. 🧪💻🧬 👉 Get yours and stabilize your system: https://bit.ly/Sinhaki The code from the video is available on GitHub: https://github.com/CodigoMaquina/code #MachineLearning #DeepLearning