XGBoost for Regression Predictive Modeling and Time Series Analysis
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XGBoost for Regression Predictive Modeling and Time Series Analysis
Learn how to build, evaluate, and deploy predictive models with expert guidance
Weiner, Joyce; Zicari, Prof. Roberto V.; Deka, Partha Pritam
Packt Publishing Limited
12/2024
308
Mole
9781805123057
Pré-lançamento - envio 15 a 20 dias após a sua edição
Descrição não disponível.
Table of Contents
An Overview of Machine Learning, Classification, and Regression
XGBoost Quick Start Guide with an Iris Data Case Study
Demystifying the XGBoost Paper
Adding On to the Quick Start - Switching Out the Dataset with a Housing Data Case Study
Classification and Regression Trees, Ensembles, and Deep Learning Models - What's Best for Your Data?
Data Cleaning, Imbalanced Data, and Other Data Problems
Feature Engineering
Encoding Techniques for Categorical Features
Using XGBoost for Time Series Forecasting
Model Interpretability, Explainability, and Feature Importance with XGBoost
Metrics for Model Evaluations and Comparisons
Managing a Feature Engineering Pipeline in Training and Inference
Deploying Your XGBoost Model
An Overview of Machine Learning, Classification, and Regression
XGBoost Quick Start Guide with an Iris Data Case Study
Demystifying the XGBoost Paper
Adding On to the Quick Start - Switching Out the Dataset with a Housing Data Case Study
Classification and Regression Trees, Ensembles, and Deep Learning Models - What's Best for Your Data?
Data Cleaning, Imbalanced Data, and Other Data Problems
Feature Engineering
Encoding Techniques for Categorical Features
Using XGBoost for Time Series Forecasting
Model Interpretability, Explainability, and Feature Importance with XGBoost
Metrics for Model Evaluations and Comparisons
Managing a Feature Engineering Pipeline in Training and Inference
Deploying Your XGBoost Model
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Table of Contents
An Overview of Machine Learning, Classification, and Regression
XGBoost Quick Start Guide with an Iris Data Case Study
Demystifying the XGBoost Paper
Adding On to the Quick Start - Switching Out the Dataset with a Housing Data Case Study
Classification and Regression Trees, Ensembles, and Deep Learning Models - What's Best for Your Data?
Data Cleaning, Imbalanced Data, and Other Data Problems
Feature Engineering
Encoding Techniques for Categorical Features
Using XGBoost for Time Series Forecasting
Model Interpretability, Explainability, and Feature Importance with XGBoost
Metrics for Model Evaluations and Comparisons
Managing a Feature Engineering Pipeline in Training and Inference
Deploying Your XGBoost Model
An Overview of Machine Learning, Classification, and Regression
XGBoost Quick Start Guide with an Iris Data Case Study
Demystifying the XGBoost Paper
Adding On to the Quick Start - Switching Out the Dataset with a Housing Data Case Study
Classification and Regression Trees, Ensembles, and Deep Learning Models - What's Best for Your Data?
Data Cleaning, Imbalanced Data, and Other Data Problems
Feature Engineering
Encoding Techniques for Categorical Features
Using XGBoost for Time Series Forecasting
Model Interpretability, Explainability, and Feature Importance with XGBoost
Metrics for Model Evaluations and Comparisons
Managing a Feature Engineering Pipeline in Training and Inference
Deploying Your XGBoost Model
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
