statistical learning data science (200 risultati)

Paperback. Condizione: New.

Condizione: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Condizione: New. Brand New, Softcover edition. This item may ship from the US or our Overseas warehouse depending on your location and stock availability.

Soft cover. Condizione: Very Good. VERY GOOD softcover, no marks in text, very clean exterior. Book.

Condizione: New.

Soft cover. Condizione: New. ISBN:9781138044852,Territorial restriction maybe printed on the book. This is an Int'l edition, ISBN and cover may differ from US edition, Contents same as US edition.

Hardback. Condizione: New.

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Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days. 204.

Paperback. Condizione: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

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Condizione: New. pp. 444.

paperback. Condizione: New.

Condizione: New. pp. 388.

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Hardcover. Condizione: new. Hardcover. This contributed volume offers practical implementation strategies for statistical learning and data science techniques, with fully peer-reviewed papers that embody insights and experiences gathered within the LISA 2020 Global Network. Through a series of compelling case studies, readers are immersed in practical methodologies, real-world applications, and innovative approaches in statistical learning and data science.Topics covered in this volume span a wide array of applications, including machine learning in health data analysis, deep learning models for precipitation modeling, interpretation techniques for machine learning models in BMI classification for obesity studies, as well as a comparative analysis of sampling methods in machine learning health applications. By addressing the evolving landscape of data analytics in many ways, this volume serves as a valuable resource for practitioners, researchers, and students alike.The LISA 2020 Global Network is dedicated to enhancing statistical and data science capabilities in developing countries through the establishment of collaboration laboratories, also known as stat labs. These stat labs function as engines for development, nurturing the next generation of collaborative statisticians and data scientists while providing essential research infrastructure for researchers, data producers, and decision-makers. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Softcover. Condizione: New. Condizione sovraccoperta: no dj. First. Statistical Inference in Data Science and Machine Learning offers a comprehensive guide to the art of statistical inference in the field of data science and machine learning. By examining the complex relationships between statistical inference, data analysis, and machine learning algorithms, this book provides a nuanced understanding of the most effective strategies for extracting insights from large datasets. From the development of statistical models to the creation of machine learning pipelines, Statistical Inference in Data Science and Machine Learning demonstrates how data scientists and machine learning engineers can harness the power of statistical inference to drive data-driven decision-making. By adopting this approach, data scientists and machine learning engineers can create data products that truly drive business value and improve customer outcomes. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condizione: New. Condizione sovraccoperta: no dj. First. Statistical methods are a critical component of machine learning and data science, enabling researchers and practitioners to extract insights and patterns from large datasets. Statistical Methods for Machine Learning and Data Science offers a comprehensive exploration of the latest techniques and technologies for using statistical methods in machine learning and data science. This book examines the ways in which statistical methods can be used to improve the accuracy and reliability of machine learning models, and provides a roadmap for researchers and practitioners to develop more effective data science strategies. By exploring the latest research and data on the topic, Statistical Methods for Machine Learning and Data Science provides a nuanced understanding of the critical role that statistical methods play in shaping the future of machine learning and data science. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condizione: New. Condizione sovraccoperta: no dj. First. Statistical Methods for Machine Learning Algorithms in Data Science is a comprehensive treatment of the statistical methods used in machine learning algorithms. The book provides a detailed examination of the statistical techniques used to develop and evaluate machine learning models, including regression, classification, clustering, and dimensionality reduction. By applying the principles of statistical inference to machine learning algorithms, this book offers a deep understanding of the underlying statistical methods and provides a framework for developing and evaluating machine learning models that are accurate, reliable, and interpretable. The book is an essential resource for data scientists and machine learning practitioners working in the field of data science and artificial intelligence. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condizione: New. Condizione sovraccoperta: no dj. First. Python and R for Statistical Analysis and Data Science and Machine Learning is a seminal work that bridges the gap between statistical analysis, data science, and machine learning. This book provides a clear and concise introduction to the fundamentals of Python and R programming, emphasizing their applications in statistical analysis, data visualization, and machine learning. By combining the strengths of both languages, the author presents a comprehensive framework for tackling complex data-driven problems. From data preprocessing to model evaluation, this guide offers practical insights and real-world examples to help readers navigate the intricacies of statistical analysis and machine learning. Whether you're a researcher, analyst, or data scientist, this book equips you with the skills to extract meaningful insights from data and drive informed decision-making. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condizione: New. Condizione sovraccoperta: no dj. First. Python and R for Statistical Analysis and Data Science and Machine Learning and Time Series Analysis is a comprehensive guide to the application of statistical analysis and machine learning in data science. This book provides an in-depth examination of the principles and techniques used in statistical analysis, from data preprocessing and feature engineering to model selection and evaluation. By exploring the intersection of statistical analysis and machine learning, this book offers a nuanced understanding of the complex relationships between data, models, and predictions. With its focus on practical solutions and real-world examples, this book provides a valuable resource for data scientists, researchers, and practitioners seeking to extract insights from complex data sets. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condizione: New. Condizione sovraccoperta: no dj. First. Data Science - A Beginner's Guide to Statistical Analysis and Machine Learning offers a comprehensive introduction to the rapidly evolving field of data science. This book provides a detailed overview of the essential concepts, techniques, and tools necessary for working with data, including statistical analysis, machine learning, and data visualization. By offering a clear and accessible explanation of complex concepts, readers will gain a deeper understanding of the power and potential of data-driven decision-making. As data becomes increasingly central to business strategy and innovation, this book provides a timely and relevant framework for professionals seeking to develop their skills and stay ahead of the curve. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condizione: New. Condizione sovraccoperta: no dj. First. This book offers a comprehensive introduction to the use of Python and R for statistical analysis, machine learning, visualization, and data science. By exploring the capabilities of these programming languages, readers will gain a deeper understanding of how to develop and implement effective statistical analysis and machine learning models. The book covers a range of topics, including data preprocessing, feature engineering, and model evaluation, all within the context of statistical analysis and machine learning. Through a series of case studies and real-world examples, readers will learn how to develop and implement effective Python and R scripts and programs that can inform statistical analysis and drive meaningful change. By mastering the concepts and techniques presented in this book, readers will be well-equipped to tackle the challenges of statistical analysis and machine learning. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

paperback. Condizione: New. Paperback. Pub Date: 2004 Pages: 381 Language: Chinese in Publisher: Publishing House of Electronics Industry of computing and information technology rapid development has brought huge amounts of data in many fields such as medicine. biology. finance and marketing. The understanding of these data is a challenge. and this led to the development of a new tool in the field of statistics. and extends to the new areas of such as data mining. machine learning. and bio-informatics. Many tools have a.

paperback. Condizione: New. Paperback. Pub Date: 2017-05-01 Pages: $number Language: Chinese Publisher: People posts and telecommunications publishing house at present. machine learning and data science are very important and popular related disciplines. need to study in depth to master. This book attempts to guide the reader on how to complete a data science project involving machine learning. This book will provide data scientists with .

paperback. Condizione: New. Language:Chinese.Paperback.Pub Date:2023-11 Publisher: Tsinghua University Press?Introduction to R and R Commander?Introduction to how to download and install the software? Demonstration of applying R Commander to a simple data analysis problem. from data input to report writing?Explanation of how Entering and manipulating data in R Commander Describes the implementation of many common statistical methods in R Commander Shows how to calculate probability distributions and perform simple simul.