LEARN XGBoost : Build High-Performance Models for Accurate Predictions
Language: English
Published by Createspace Independent Publishing Platform Apr 2025, 2025
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
US$ 25.55
Quantity: 2 available
Add to basketItem description from seller
Neuware - Mastering XGBoost is an essential skill for professionals working in data science, machine learning, and predictive model engineering in critical environments. Widely used in technical competitions, business solutions, and large-scale production systems, XGBoost is a leading reference for performance, stability, and control in supervised learning pipelines. This book offers a direct, applied, and technically precise approach to all core aspects of the library, focusing on real-world applications and professional validation.Developed in accordance with the TECHWRITE 2.3 Protocol, the content is ideal for data scientists, machine learning engineers, technical analysts, and students seeking to master XGBoost with an operational focus and full system integration. Its modular structure allows for a progression from conceptual understanding to technical deployment, with explained code, recommended practices, and structured error resolution.You will learn how to build robust models for classification, regression, and multiclass problems, with advanced evaluation, automated tuning, and integration into production environments.Includes: Structured data pipelines using Pandas and NumPySupervised modeling with XGBClassifier and XGBRegressorTuning with GridSearchCV, RandomizedSearchCV, and cross-validationExplainability using SHAP Values, importance_gain, and visualizationsTime series forecasting with sliding windowsDeployment via Flask, FastAPI, Streamlit, and DockerGPU (CUDA) execution and Dask clustersIntegration with AWS SageMaker and enterprise modelingCase studies using public datasets and a final professional checklistMaster XGBoost and position yourself with technical authority in projects that demand accurate predictions, reliable validation, and end-to-end delivery aligned with systems and strategic objectives. This book is your professional reference manual for the most powerful algorithm in modern supervised modeling.xgboost, supervised machine learning, classification and regression, hyperparameter tuning, deployment with Flask and FastAPI, SHAP Values, time series, Dask, GPU, SageMaker, enterprise projects, explainability, predictive modeling, production pipelines.…
Seller Inventory # 9798281647175
- Title
- LEARN XGBoost : Build High-Performance Models for Accurate Predictions
- Author
- Studiod Smart Tech Content
- Publisher
- Createspace Independent Publishing Platform Apr 2025
- Publication year
- 2025
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798281647175
- Item weight
- 232 grams
- Dimensions
- 229x152x12 mm
- Series
- Book 11 of 15: AI & Machine Learning ENG
Mastering XGBoost is an essential skill for professionals working in data science, machine learning, and predictive model engineering in critical environments. Widely used in technical competitions, business solutions, and large-scale production systems, XGBoost is a leading reference for performance, stability, and control in supervised learning pipelines. This book offers a direct, applied, and technically precise approach to all core aspects of the library, focusing on real-world applications and professional validation.
Developed in accordance with the TECHWRITE 2.3 Protocol, the content is ideal for data scientists, machine learning engineers, technical analysts, and students seeking to master XGBoost with an operational focus and full system integration. Its modular structure allows for a progression from conceptual understanding to technical deployment, with explained code, recommended practices, and structured error resolution.
You will learn how to build robust models for classification, regression, and multiclass problems, with advanced evaluation, automated tuning, and integration into production environments.
Includes:
Structured data pipelines using Pandas and NumPy
Supervised modeling with XGBClassifier and XGBRegressor
Tuning with GridSearchCV, RandomizedSearchCV, and cross-validation
Explainability using SHAP Values, importance_gain, and visualizations
Time series forecasting with sliding windows
Deployment via Flask, FastAPI, Streamlit, and Docker
GPU (CUDA) execution and Dask clusters
Integration with AWS SageMaker and enterprise modeling
Case studies using public datasets and a final professional checklist
Master XGBoost and position yourself with technical authority in projects that demand accurate predictions, reliable validation, and end-to-end delivery aligned with systems and strategic objectives. This book is your professional reference manual for the most powerful algorithm in modern supervised modeling.
xgboost, supervised machine learning, classification and regression, hyperparameter tuning, deployment with Flask and FastAPI, SHAP Values, time series, Dask, GPU, SageMaker, enterprise projects, explainability, predictive modeling, production pipelines
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