MACHINE LEARNING - Algoritmos de Clasificación
Horario: martes y jueves de 14 a 18  
Comienzo: martes 7 de abril
Fechas: 7, 9,14, 16, 21, 23, 28 y 30 de abril
LUGAR: Sede Lima (Lima e Hipólito Yrigoyen)
Horas: 32 en 8 clases de cuatro horas

TRAETE TU NOTEBOOK PARA CODEAR

HIPÓLITO YRIGOYEN 1144 - PRIMER PISO - OFICINA 3

ARANCEL DEL CURSO: $5.900
Precio abonando antes del 31 de marzo: $4.900

MACHINE LEARNING - Algoritmos de Clasificación

A lo largo del curso construiremos 10 proyectos prácticos usando Python y Scikit Learn

What is Machine Learning?

Logistic Regression

Logistic Regression Introduction and Learning Outcomes
Logistic Regression Intuition
Confusion Matrix Overview
Logistic Regression - Project #1
Logistic Regression - Project #2 Overview
Logistic Regression - Project #2


Support Vector Machines

Support Vector Machines Intro and Learning Outcomes
Support Vector Machines - Intuition
Support Vector Machines - Project #1
Support Vector Machines - Project #2 Overview
Support Vector Machines - Project #2

K-Nearest Neighbors

K-Nearest Neighbors Intro and Learning Outcomes
K-Nearest Neighbors - Intuition
KNN - Project #1
KNN - Project #2 Overview
KNN - Project #2

Decision Trees and Random Forest

Decision Trees and Random Forest Intro and Learning Outcomes
Decision Trees - Intuition
Random Forest - Intuition
Decision Trees & Random Forest - Project #1
Decision Trees & Random Forest - Project #2 Overview
Decision Trees & Random Forest - Project #2

Naive Bayes Classifiers

Naive Bayes Intro and Learning Outcomes
Naive Bayes Intuition
Naive Bayes - Mathematics
Naive Bayes - Project #1
Naive Bayes - Project #2 - Overview
Naive Bayes - Project #2 - Part #1