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  1. Mechanistic modelling essentials
    Mechanistic modelling essentials
    Principles, mathematics and statistics for building and applying TK and TKTD models
    Tjalling Jager

    Would you like to use TK or TKTD modelling to answer (applied) scientific questions, but lack the background in modelling and/or statistics? Then this is the book for you. This book provides a small selection of the tools from math and stats, along with some elements from philosophy of science, to get you up to speed.

  2. Linear Algebra
    Linear Algebra
    OpenIntro and Jim Hefferon

    If you are able to contribute, it will go to support OpenIntro (not the author), a US-based nonprofit working to spread open materials, e.g. by providing desk copies to instructors considering this text. This listing is in collaboration with the textbook's author, Jim Hefferon. Linear Algebra's official websitePaperbacks are $22openintro.org

  3. Essays on Data Analysis

    This book draws a complete picture of the data analysis process, filling out many details that are missing from previous presentations. It presents a new perspective on what makes for a successful data analysis and how the quality of data analyses can be judged.

  4. Data Visualization Using Tableau for Data Scientists

    Turn data into decisions. Data Visualization Using Tableau for Data Scientists shows how interactive visuals, analytics, and storytelling come together to make complex data understandable, actionable, and impactful.

  5. APEX Calculus
    APEX Calculus
    4th Edition
    OpenIntro and Gregory Hartman

    Leanpub revenue supports OpenIntro. OpenIntro is a US-based nonprofit that provides textbook services to help increase adoption of OER textbooks and save students money. These textbook services are fully financed by Leanpub contributions on supported books. APEX Calculus website: apexcalculus.comOpenIntro website: openintro.org

  6. Principles of fMRI
    Principles of fMRI
    Tor D. Wager and Martin A. Lindquist

    Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. This book covers the design, acquisition, and analysis of fMRI data.

  7. Applied Conformal Prediction:Practical Uncertainty Quantification for Real-World ML
    Applied Conformal Prediction:Practical Uncertainty Quantification for Real-World ML
    Practical Uncertainty Quantification for Real-World ML Learn Conformal Prediction (CP), the state-of-the-art technique for building statistically valid, model-agnostic prediction intervals
    Valery Manokhin

    A powerful new book on Conformal Prediction by bestselling author and machine learning expert Valery Manokhin, bridging theory and real-world machine learning. Discover how to quantify uncertainty with statistical guarantees—across deep learning, time series, forecasting, and more. Preorder now before the price goes up.

  8. Big open questions in TKTD modelling
    Big open questions in TKTD modelling
    (and some not so big ones)
    Tjalling Jager

    Toxicokinetic-toxicodynamic (TKTD) modelling is an exciting field of ecotoxicology that aims to understand and predict toxic effects, rather than just describing them. A lot of work has been done in this field, especially over the last two decades. However, many open (and in some cases fundamental) questions still remain to be solved.

  9. Data Analysis for the Life Sciences
    Data Analysis for the Life Sciences
    Rafael A Irizarry and Michael I Love

    Data analysis is now part of practically every research project in the life sciences. In this book we use data and computer code to teach the necessary statistical concepts and programming skills to become a data analyst. Instead of showing theory first and then applying it to toy examples, we start with actual applications and describe the theory as it becomes necessary to solve specific challenges. The book includes links to computer code that readers can use to follow along as they program.

  10. Introductory Statistics with Randomization and Simulation
    Introductory Statistics with Randomization and Simulation
    OpenIntro, David Diez, Mine Cetinkaya-Rundel, and Christopher Barr

    A complete foundation for Statistics, also serving as a foundation for Data Science, that introduces inference using randomization and simulation while covering traditional methods. Leanpub revenue supports OpenIntro, so we can provide free desk copies to teachers interested in using our books in the classroom. More resources: openintro.org.

  11. Supervised Machine Learning for Science
    Supervised Machine Learning for Science
    How to stop worrying and love your black box
    Christoph Molnar and Timo Freiesleben

    This book explores supervised machine learning for scientific research, addressing its limitations in interpretability, causality, and uncertainty quantification. By unifying philosophical justification with practical solutions, it provides a roadmap for turning machine learning into a rigorous tool for science.

  12. Life in the Lab, the essential guide to becoming a researcher
    Life in the Lab, the essential guide to becoming a researcher
    Experimental design, conducting research, data analysis and statistics, and writing up your work for publication
    Kevin Hamill

    New to research? This is the one book you should read. It's got everything. It'll take you from choosing your project and starting out in a lab, through designing experiments, acquiring data and performing the appropriate analysis, and all the way on to writing up your work for publication, and presenting your work at conferences.

  13. Quantum Computing for Software Engineers

    Quantum computing is real, but is frankly surrounded by a thick fog of hype. Do you want to see it clearly, understand its realities, and even consider joining it as a professional software engineer?

  14. How to be a modern scientist

    A book about how to be a scientist the modern, open-source way.

  15. Sensory Codex ( Nature : The big scientist )

    Nature has already run the experiments. We just need to copy the results. Before human engineers built sensors, evolution spent millions of years perfecting them.Sensory Codex – Nature: The Big Scientist decodes 500 extraordinary biological mechanisms that bridge the gap between biology and the technologies of tomorrow. Ready to look at life through a different lens?