Data Science Model Books
Explore tailored Data Science Model books created by our AI
One Hot Encoding Mastery
Transform Categorical Data Into Machine Learning Gold
Navigate the critical intersection of data preparation and machine learning success. This guide takes you through the complete landscape of one hot encoding—from foundational concepts to advanced optimization strategies. You'll discover why this seemingly simple technique is essential for working with categorical data, explore the mathematical principles that make it work, and learn when alternative approaches might serve your models better. The book addresses real-world challenges: handling high-cardinality features, managing unseen categories in production, and optimizing memory usage with sparse representations. Through practical examples and clear explanations, you'll understand how encoding decisions ripple through your entire machine learning pipeline. Whether you're building recommendation systems, classification models, or predictive analytics applications, this comprehensive resource equips you with the knowledge to make informed preprocessing decisions that directly impact model accuracy and performance.
You'll move from understanding PyTorch fundamentals to building production-ready deep learning models that solve real biological challenges. This book guides you through the complete workflow of computational biology projects: from formulating biological questions as machine learning problems, through data acquisition and preprocessing, to model development, validation, and deployment. You'll learn how to work with diverse biological data types—genomic sequences, protein structures, medical images, and time-series measurements—using PyTorch's flexible architecture. Each chapter combines theoretical foundations with practical code examples, showing you how to handle the messy realities of biological data including class imbalance, missing values, and limited samples. You'll discover how to leverage transfer learning, implement custom loss functions for biological objectives, and validate models using domain-specific metrics. By the end, you'll have the skills to design computational solutions that bridge the gap between cutting-edge machine learning and meaningful biological discovery.
Taming the Dimensional Beast
Mastering the Curse of Dimensionality in AI and Machine Learning
Dive into the intricate world of high-dimensional data and its impact on AI and machine learning. This book takes you on an enlightening exploration of the curse of dimensionality, a phenomenon that can significantly affect the performance and efficiency of your machine learning models. You'll gain a deep understanding of how the curse of dimensionality manifests in various aspects of data analysis and model building. From feature scaling techniques to dimensionality reduction methods, you'll discover practical strategies to mitigate its effects and improve your models' accuracy and computational efficiency. Through real-world examples and hands-on exercises, you'll learn to identify when the curse of dimensionality is affecting your projects and how to apply the right techniques to overcome it. By the end of this book, you'll have the knowledge and tools to confidently handle high-dimensional datasets and optimize your machine learning workflows.
You'll gain practical mastery of unsupervised machine learning by understanding how to extract meaningful insights from unlabeled data. This book walks you through the core algorithms—clustering, dimensionality reduction, and anomaly detection—with clear explanations of when and why to use each technique. You'll learn the mathematical foundations without getting lost in complex notation, explore real-world applications across customer segmentation, image analysis, and recommendation systems, and discover how to evaluate your models when ground truth labels don't exist. Each chapter combines theory with hands-on examples, showing you how to preprocess data, select appropriate algorithms, tune hyperparameters, and interpret results. Whether you're preparing data for supervised learning or building standalone unsupervised systems, this book equips you with the knowledge and confidence to tackle complex pattern discovery challenges in your own projects.
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What if your app could serve twice as many users simply by making it accessible? Millions of people with disabilities want to use Android apps but face barriers created by poor design choices. This book shows you how to remove those barriers and build applications that work seamlessly for everyone. You'll learn the practical techniques for implementing screen reader support, voice control, and other assistive technologies. Discover how semantic markup, proper content descriptions, and inclusive design patterns create apps that are easier to use for all users. Through real-world examples and step-by-step guidance, you'll master the Android Accessibility Framework and understand WCAG 2.1 standards. Learn testing strategies that reveal accessibility issues before your users encounter them. By the end, you'll have the knowledge to make accessibility a core part of your development process, not an afterthought—expanding your market reach while creating genuinely inclusive digital experiences.
Imagine delivering software that consistently meets stakeholder expectations, where every feature works exactly as intended, and your team moves with confidence through changes and refactoring. This is the reality when you master acceptance test-driven development. This comprehensive guide takes you beyond the basics to show you how ATDD transforms the way teams develop software. You'll learn how to write acceptance tests that serve as living documentation, collaborate effectively with business stakeholders to define clear acceptance criteria, and integrate ATDD seamlessly into your Extreme Programming workflow. Whether you're struggling with unclear requirements, dealing with late-stage defect discovery, or simply want to elevate your development practices, this book provides practical strategies, real-world examples, and proven techniques. You'll understand not just the "how" but the "why" behind acceptance test-driven development, enabling you to make informed decisions about implementation in your own context. Master this essential XP practice and watch your team's productivity and code quality soar.
Take your TypeScript skills from intermediate to advanced in just 30 days with a structured, project-driven approach. This book guides you through focused techniques that matter most: mastering advanced types like generics and conditional types, writing reliable async code with proper error handling, integrating TypeScript with modern frameworks, and building confidence through comprehensive testing strategies. Each day builds on the previous one, combining theory with hands-on coding projects that you'll actually use. You'll refactor real code, understand why type safety matters, and develop the patterns that separate good TypeScript developers from great ones. By day 30, you'll have the skills to write safer, more maintainable code and the portfolio projects to prove it. This isn't theory—it's practical, accelerated learning designed for developers ready to level up.
Discover how to build software that meets expectations from day one. Acceptance test-driven development (ATDD) transforms how teams define, test, and deliver quality software by writing acceptance tests before development begins. This practical guide shows you how to collaborate with stakeholders to define clear acceptance criteria, automate those criteria into executable tests, and use them to guide development and beta testing efforts. You'll learn to bridge the communication gap between business requirements and technical implementation, reduce costly defects discovered late in the cycle, and create living documentation that keeps pace with your product. Whether you're a QA professional, beta tester, or developer, this book provides actionable strategies, real-world examples, and proven frameworks to implement ATDD in your organization. Move beyond traditional testing approaches and join teams that are catching defects earlier, improving stakeholder alignment, and delivering software with confidence.
Building systems that reliably handle data is one of the hardest challenges in backend development. Without a solid understanding of ACID properties, you risk data corruption, lost transactions, and system failures that cascade through your application. This book demystifies the four pillars of database reliability—Atomicity, Consistency, Isolation, and Durability—and shows you exactly how to apply them in real-world scenarios. You'll learn why these properties matter, how they work under the hood, and how to leverage them when designing transactions, choosing databases, and handling failures. Whether you're building a financial system that can't afford to lose a penny or a high-traffic application that needs to scale, understanding ACID properties gives you the confidence to make architectural decisions that keep your data safe and your systems running smoothly.
Create a Data Science Model Book Tailored to You
Create an AI-crafted book tailored to your goals, interests, and background
Benefits of AI-tailored books
- Read one book, not ten:
- all the Data Science Model knowledge you need, gathered into a single book.
- Save days of learning:
- tell us your goals, choose your topics, and the whole book is built around them.
- Learn effortlessly:
- Data Science Model book written for your specific background and expertise.
- Understand at a glance:
- includes charts, tables, timelines, checklists, decision trees, and more.
- Stay current:
- written the day you order it, not years ago.
- Trust what you read:
- every book is checked for accuracy, with real research when your subject needs it.
Create your unique book in 3 steps
- 1. Select your focus
Select the focus of your Data Science Model book and share your background
- 2. Personalize your book
Specify your goals and choose sub-topics to include
- 3. Get your tailored book
Your book is ready in 10 minutes. Read it online, download as EPUB or PDF, or send to Kindle.
Start from a template
Frequently asked questions
- What is TailoredRead?
TailoredRead creates complete, full-length nonfiction ebooks, written specifically for you. Tell us what you want to learn and why, and TailoredRead writes you a complete ebook on it, with charts, tables, and diagrams throughout. Read it online, on Kindle, or on any e-reader, or download it as a PDF or EPUB. Every book is written fresh the day you order it.
- How is the book tailored to me?
Before anything is written, you answer a few short questions about your goals, your background, and the topics you care about. Your book is then planned around your answers: written at your level, focused on your goals, and covering the topics you chose, instead of the one-size-fits-all book a store sells everyone.
- Will it read like generic AI content?
No. Your book isn't a chat transcript: it's planned chapter by chapter before a single word is written, told in a clear book voice, and explains ideas visually with charts, tables, and diagrams. After writing, every book goes through an editorial pass that polishes chapters so the book reads consistent from start to finish. Judge for yourself: browse thousands of sample books on our Explore Books page.
- How accurate is the content?
Our AI first checks whether your subject needs live research. Niche and fast-moving subjects are researched before writing, and the book plan and chapters are grounded in what it finds. After writing, every book goes through a quality pass that checks its facts and consistency, and researched books list their sources in a Notes section at the back.
- How long is the book?
You choose the length: Comprehensive (250-300 pages), Detailed (150-200 pages), Essential (70-100 pages), or Short (30-50 pages).
- Does the book include visuals?
Yes. Every book includes charts, tables, and diagrams: timelines, checklists, step-by-step guides, decision trees, comparison tables, matrices, and bar charts. A typical book includes dozens of these visual elements.
- Can I read it on Kindle? What formats can I download?
Yes. Every book can be read in our online reader or downloaded as a PDF or EPUB. The EPUB can be opened with Kindle, Apple Books, Kobo, and any e-reader. The Commercial and Author licenses also include an editable Word (DOCX) and Markdown download.
- How much does it cost?
About the price of a regular ebook. The exact price depends on your book's length and complexity, from $2 for the shortest books to $35 for the most comprehensive, and it's shown when you review your book, before you commit to anything. Each book is a one-time purchase, yours to keep, no subscription. Licenses that let you share, teach, or publish your book range from $35.99 to $49.99.
- Can I preview the book before purchasing?
Before you pay, you'll see what your book will cover: the title, a detailed description, the estimated length, and the complete chapter-by-chapter table of contents, so you know what you're getting before you decide. The full text itself is written after you purchase.
- How long does it take to create a book?
About 10 minutes. You can start reading the opening chapters while the rest is still being written.