This is the direct expulsion of an emotional, physical and mental journey through pornography addiction. If you are a Christian seeking freedom from pornography addiction, it is my hope that this book may find you. Perhaps this book can offer something on your journey of faith in Christ Jesus. Jesus can lead you to freedom.

Confessions of a Former Pornography Addict: How Jesus Christ Made Me a New Man

Religion & Spirituality

Bruce, Andrew

Christian Books & Bibles

lulu.com

Learn how to define, develop, and implement a dynamic business strategy with "Strategic Thinking". This concise and informative guide shows you how to plan short- and long-term objectives, how to put together the right team for the right job, how to communicate your vision, and how to maintain a flexible approach by monitoring past performance and predicting future trends. It covers the essential tools of strategic management from SWOT analysis and feasibility studies to budgeting forecasts to give you a competitive edge in today's fast-moving business world.

Strategic Thinking

Business & Money

Langdon, Ken.

Management & Leadership

Dorling Kindersley Publishers Ltd.

Langford's Basic Photography: The Guide for Serious Photographers

This seminal photography text, now in its 11th edition, has been revamped, reorganized, and modernized to include the most up-to-date and need to know information for photographers. Introducing all the key concepts and fundamentals of photography, this book is a must have for any photographer's bookcase. Providing examples and practical information throughout to allow photographers to apply concepts to their own work, the text explains the fundamentals of photography in an accessible way. Fully updated to reflect the dynamic changes in the industry, this 11th edition includes expanded and updated content focusing on advances in camera technology and digital lighting, connecting with the global photography industry and professional networks through social media, updated images throughout, and a new chapter on new digital outputs. Ideal as a foundational text for students of photography as well as a key reference for professionals.

Arts & Photography

LANGFORD, MICHAEL

Fox, Anna

Sawdon Smith, Richard

Photography & Video

Routledge

Statistical methods are a key part of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.
Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.
With this book, you’ll learn:
<ul>
<li>Why exploratory data analysis is a key preliminary step in data science</li>
<li>How random sampling can reduce bias and yield a higher quality dataset, even with big data</li>
<li>How the principles of experimental design yield definitive answers to questions</li>
<li>How to use regression to estimate outcomes and detect anomalies</li>
<li>Key classification techniques for predicting which categories a record belongs to</li>
<li>Statistical machine learning methods that “learn” from data</li>
<li>Unsupervised learning methods for extracting meaning from unlabeled data</li>
</ul>

Practical Statistics for Data Scientists: 50 Essential Concepts

Computers & Technology

Bruce, Peter

Programming

O'Reilly Media

<div> Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you'll learn: <ul> <li>Why exploratory data analysis is a key preliminary step in data science</li> <li>How random sampling can reduce bias and yield a higher-quality dataset, even with big data</li> <li>How the principles of experimental design yield definitive answers to questions</li> <li>How to use regression to estimate outcomes and detect anomalies</li> <li>Key classification techniques for predicting which categories a record belongs to</li> <li>Statistical machine learning methods that "learn" from data</li> <li>Unsupervised learning methods for extracting meaning from unlabeled data</li> </ul> </div>

Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python

Gedeck, Peter

Reference

Los métodos estadísticos son una parte fundamental de la ciencia de datos, pero pocos científicos de datos tienen una formación avanzada en estadística. Los cursos y libros sobre estadística básica rara vez tratan el tema desde la perspectiva de la ciencia de datos. La segunda edición de este libro incluye ejemplos detallados de Python, ofrece una orientación práctica sobre la aplicación de los métodos estadísticos a la ciencia de datos, te indica cómo evitar su uso incorrecto y te aconseja sobre lo que es y lo que no es importante. Muchos recursos de la ciencia de datos incorporan métodos estadísticos, pero carecen de una perspectiva estadística más profunda. Si estás familiarizado con los lenguajes de programación R o Python y tienes algún conocimiento de estadística, este libro suple esas carencias de una forma práctica, accesible y clara. Con este libro aprenderás: Por qué el análisis exploratorio de datos es un paso preliminar clave en la ciencia de datos Cómo el muestreo aleatorio puede reducir el sesgo y ofrecer un conjunto de datos de mayor calidad, incluso con Big Data Cómo los principios del diseño experimental ofrecen respuestas definitivas a preguntas Cómo utilizar la regresión para estimar resultados y detectar anomalías Técnicas de clasificación esenciales para predecir a qué categorías pertenece un registro Métodos estadísticos de aprendizaje automático que 'aprenden' a partir de los datos Métodos de aprendizaje no supervisados para extraer significado de datos sin etiquetar Peter Bruce es el fundador del Institute for Statistics Education en Statistics.com. Andrew Bruce es científico investigador jefe en Amazon y tiene más de 30 años de experiencia en estadística y ciencia de datos. Peter Gedeck es científico de datos senior en Collaborative Drug Discovery, desarrolla algoritmos de aprendizaje automático para pronosticar propiedades de posibles futuros fármacos.

Estadística práctica para ciencia de datos con R y Python

Programming Languages

Marcombo

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