PROGRAMMING MACHINE LEARNING IN PYTHON: An Introduction to Machine Learning Models - Supervised - Couverture souple

Gómez, Jorge; Hernández, Velssy

Couverture souple

ISBN 10 : 6205365235 ISBN 13 : 9786205365236

Editeur : Our Knowledge Publishing, 2022

Synopsis

Supervised learning describes a scenario in which experience becomes a training factor, which contains important information (e.g., sick/healthy labels for plant disease detection) that is missing from the unseen "test examples" to which the learned expertise will be applied. In this scenario, the learned expertise aims to predict that missing information for the test data. In this sense, the environment can be thought of as a teacher who supervises the learner by providing additional information, which are the labels. In this book we will deal with supervised machine learning models, through which you will understand the theoretical foundations, some descriptions of application fields and then implement each of them in Jupyter lab with pandas and scikit-learn libraries for Python. Initially you will start with Logistic Regression (binary classification), Multiclass Classification by Logistic Regression, Decision Trees, Support Vector Machine - SVM (Support Vector Machines), Random Forest, K-Fold Cross Validation and finally Naive B

Détails de l'édition

• Éditeur: Our Knowledge Publishing
• Date d'édition: 2022
• Langue: anglais
• ISBN 10: 6205365235
• ISBN 13: 9786205365236
• Reliure: Broché
• Nombre de pages: 104
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible