Master the Proven Framework for Small Business Growth and Long-Term Success

About the Book

Running a small business shouldn’t feel like chaos. In How to Grow Your Small Business, bestselling author and entrepreneur Donald Miller cuts through the noise and delivers a clear, actionable system for sustainable growth. Drawing from years of building successful companies and coaching thousands of business owners, Miller shows you exactly how to create structure, clarity, and momentum in your business. This isn’t theory—it’s a proven framework that transforms overwhelmed entrepreneurs into confident leaders who run profitable, scalable companies.

From the Back Cover

Stop guessing and start growing. This book hands you the blueprint for turning your small business into a thriving enterprise that works for you, not against you.

About the Author

Donald Miller is a renowned business coach, speaker, and CEO who has helped thousands of small business owners clarify their message and grow their companies. As the founder of StoryBrand and Business Made Simple, Miller combines storytelling expertise with practical business strategy. His frameworks are used by entrepreneurs worldwide to create clarity, increase revenue, and build teams that execute with purpose. Miller’s approach is refreshingly simple: give business owners the tools they need to succeed without the MBA jargon.

Who Is This Book For?

This book is perfect for small business owners who feel stuck, overwhelmed, or uncertain about how to grow sustainably. If you’re an entrepreneur struggling to scale beyond six or seven figures, a solopreneur ready to build a team, or a business leader looking for a proven system to bring order to the chaos, this book is your roadmap. It’s also ideal for anyone who wants to lead with confidence, create repeatable success, and build a business that doesn’t depend on their constant presence to survive.

Frequently Asked Questions (FAQs)

Q: What will I learn from Donald Miller’s How to Grow Your Small Business?
You’ll learn a proven system for scaling your small business, including how to create clarity in your operations, build effective teams, implement growth strategies, and develop leadership skills that drive sustainable success.

Q: Is this book good for startups or only established small businesses?
This book works for both. Whether you’re launching a startup or running an established business that’s hit a growth plateau, Miller’s framework helps you build structure and momentum at any stage.

Q: How is Donald Miller’s business growth system different from other books?
Miller focuses on simplicity and execution. Instead of overwhelming theory, you get practical tools and frameworks used by thousands of successful entrepreneurs. It’s designed for busy business owners who need results, not fluff.

Q: Do I need business experience to understand this book?
No MBA required. Miller writes in clear, accessible language that any small business owner can understand and apply immediately. The strategies are practical and designed for real-world implementation.

Weight

320 g

Dimensions

21.8 × 13.5 × 1.3 cm

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Essential Math for Data Science By Thomas Nield

Name: Buy Essential Math for Data Science by Thomas Nield
SKU: BW-0011142
Price: 26.99 USD
Availability: InStock

Original price was: $37.10.Current price is: $26.99.

Binding: Paperback
Language: English
ISBN-13:978-9355422743
Reader’s Age: Adults 18+ (Students, Professionals, Career Changers)
Ships Within: 5–10 Business Days
Author: Thomas Nield
Release Date: July 5, 2022
Genre: Educational & Academic

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Description

Learn the Fundamental Mathematics You Need to Succeed in Data Science and Machine Learning

About the Book

Essential Math for Data Science is your roadmap to understanding the mathematical concepts that drive modern data science and machine learning. Written by Thomas Nield and published by O’Reilly Media, this book demystifies statistics, linear algebra, calculus, and probability through practical, real-world applications. Instead of drowning you in proofs and theory, it focuses on what you actually need to know to work with data, build models, and communicate insights effectively. Each chapter includes Python code examples that reinforce learning and help you apply concepts immediately.

About the Author

Thomas Nield is a data science instructor, consultant, and author known for making complex technical subjects accessible to learners at all levels. With years of experience teaching professionals how to transition into data-driven roles, Thomas has a gift for breaking down intimidating topics into practical, understandable lessons. His work with O’Reilly Media has helped thousands of students bridge the gap between theory and real-world application in data science and analytics.

Who Is This Book For?

This book is ideal for aspiring data scientists, software developers transitioning into machine learning, business analysts looking to deepen their technical skills, and students preparing for careers in AI and analytics. Whether you’re self-taught or coming from a non-mathematical background, this guide meets you where you are and builds your confidence step by step. If you’ve ever felt intimidated by the math in data science courses or struggled to understand why certain algorithms work, this book will finally make everything click.

Frequently Asked Questions (FAQs)

Q: Do I need a strong math background to understand this book?
No. Essential Math for Data Science is designed for beginners and professionals without advanced math degrees. Thomas Nield explains concepts from the ground up using plain language and practical examples, making it perfect for self-learners and career changers.

Q: Does this book include Python code examples?
Yes. Each mathematical concept is accompanied by Python code that demonstrates how to apply the theory in real data science scenarios. You’ll work with libraries like NumPy and understand how math translates into working code.

Q: What topics in math for data science does this book cover?
The book covers essential topics including descriptive and inferential statistics, linear algebra (vectors, matrices, eigenvalues), calculus (derivatives, gradients, integrals), and probability theory. These are the core mathematical foundations needed for machine learning and data analysis.

Q: Is this book suitable for preparing for data science interviews?
Absolutely. Understanding the math behind algorithms is a common interview topic for data science roles. This book helps you explain concepts like gradient descent, loss functions, and matrix operations with confidence, giving you an edge in technical interviews.

Q: How is this different from academic math textbooks?
Unlike traditional textbooks that focus on proofs and abstract theory, Essential Math for Data Science prioritizes practical application. It teaches you the math you’ll actually use in data science work, with a focus on intuition, visualization, and hands-on coding rather than memorizing formulas.

Additional information

Weight	650 g
Dimensions	17.78 × 1.65 × 22.86 cm

Short Summary

You'll learn how statistics help you understand and interpret data patterns, how linear algebra powers machine learning models and transformations, why calculus is essential for optimization and gradient descent, and how probability theory enables you to make predictions under uncertainty. By the end, you'll have the mathematical literacy to read research papers, understand algorithm documentation, and confidently tackle real-world data science challenges with Python.