Name: Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis (en Inglés)
Price: 202664.00 COP
Availability: InStock
Author: Paul Hoang
ISBN: 9781804614280

portada Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis (en Inglés)

Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis (en Inglés)

Formato

Libro Físico

Autor

Editorial

Idioma

Inglés

N° páginas

420

Encuadernación

Tapa Blanda

Dimensiones

23.5 x 19.1 x 2.2 cm

Peso

0.72 kg.

ISBN13

9781804614280

Categorías

Probabilidad y estadística
Diseño y teoría de bases de datos
Arquitectura de la información

Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis (en Inglés)

Paul Hoang (Autor) · Huy Hoang Nguyen (Autor) · Paul N. Adams (Autor) · Stuart J. Miller (Autor) · Packt Publishing · Tapa Blanda

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Reseña del libro "Building Statistical Models in Python: Develop useful models for regression, classification, time series, and survival analysis (en Inglés)"

Make data-driven, informed decisions and enhance your statistical expertise in Python by turning raw data into meaningful insightsPurchase of the print or Kindle book includes a free PDF eBookKey Features: Gain expertise in identifying and modeling patterns that generate successExplore the concepts with Python using important libraries such as stats modelsLearn how to build models on real-world data sets and find solutions to practical challengesBook Description: The ability to proficiently perform statistical modeling is a fundamental skill for data scientists and essential for businesses reliant on data insights. Building Statistical Models with Python is a comprehensive guide that will empower you to leverage mathematical and statistical principles in data assessment, understanding, and inference generation.This book not only equips you with skills to navigate the complexities of statistical modeling, but also provides practical guidance for immediate implementation through illustrative examples. Through emphasis on application and code examples, you'll understand the concepts while gaining hands-on experience. With the help of Python and its essential libraries, you'll explore key statistical models, including hypothesis testing, regression, time series analysis, classification, and more.By the end of this book, you'll gain fluency in statistical modeling while harnessing the full potential of Python's rich ecosystem for data analysis.What You Will Learn: Explore the use of statistics to make decisions under uncertaintyAnswer questions about data using hypothesis testsUnderstand the difference between regression and classification modelsBuild models with stats models in PythonAnalyze time series data and provide forecastsDiscover Survival Analysis and the problems it can solveWho this book is for: If you are looking to get started with building statistical models for your data sets, this book is for you! Building Statistical Models in Python bridges the gap between statistical theory and practical application of Python. Since you'll take a comprehensive journey through theory and application, no previous knowledge of statistics is required, but some experience with Python will be useful.

Paul Hoang

(Autor)

Ver Página del Autor

Paul Hoang es un educador con más de 25 años de experiencia en la enseñanza de Economía y Gestión Empresarial. Ha ocupado cargos como subdirector y coordinador del Programa del Diploma del Bachillerato Internacional en una reconocida escuela internacional en Hong Kong.

Es autor de varios libros de texto de éxito, entre ellos Business Management 4th Edition (2018) y Economics for the IB Diploma Revision Guide (2014). Además, ha contribuido como editor asociado en revistas especializadas como IB Review y Business Review.

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