Data Management for Natural Scientists: A Practical Guide on Data Extraction and Storage with Python, Matthias Hofmann
Автор: Strang Gilbert Название: Linear Algebra and Learning from Data ISBN: 0692196382 ISBN-13(EAN): 9780692196380 Издательство: Cambridge Academ Рейтинг: Цена: 66520.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.
Автор: Guido Sarah Название: Introduction to Machine Learning with Python ISBN: 1449369413 ISBN-13(EAN): 9781449369415 Издательство: Wiley Рейтинг: Цена: 63350.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions.
Автор: Agresti, Alan, Название: Foundations of statistics for data scientists : ISBN: 0367748452 ISBN-13(EAN): 9780367748456 Издательство: Taylor&Francis Рейтинг: Цена: 91860.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book shows the elements of statistical science that are highly relevant for students who plan to become data scientists. However, most of the content focuses on the statistical methods and the theory behind them, rather than on data science.
Автор: Subasi, Abdulhamit Название: Practical Machine Learning For Data Analysis Using Python ISBN: 0128213795 ISBN-13(EAN): 9780128213797 Издательство: Elsevier Science Рейтинг: Цена: 110030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Practical Machine Learning for Data Analysis Using Python is a problem solver's guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems.
Автор: Kaptein Maurits, Van Den Heuvel Edwin Название: Statistics for Data Scientists: An Introduction to Probability, Statistics, and Data Analysis ISBN: 303010530X ISBN-13(EAN): 9783030105303 Издательство: Springer Рейтинг: Цена: 41920.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students.
Foundational skills related to Company, Colleagues, Storytelling, Expectations, Results and Careers--emphasizing how each topic relates to your unique position as an analytics professional.
Автор: Goltz, Nachshon (Sean) Название: Real World AI Ethics for Data Scientists ISBN: 1032275065 ISBN-13(EAN): 9781032275062 Издательство: Taylor&Francis Рейтинг: Цена: 163330.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Goltz, Nachshon (sean) Dowdeswell, Tracey Название: Real world ai ethics for data scientists ISBN: 1032275057 ISBN-13(EAN): 9781032275055 Издательство: Taylor&Francis Рейтинг: Цена: 43890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In the midst of the 4th industrial revolution, big data is weighed in gold, placing enormous power in the hands of data scientists - the modern AI alchemists. This book seeks to shape, in a practical, diverse and inclusive way, the ethical compass of those entrusted with big data.
A good data scientist knows how to do something really well, but a great data scientist can do "something of everything." From raw data all the way to shining in front of C-level executives, a great data scientist has the skills to architect data systems, build applications, perform modeling and machine learning and wrap up the results in a clear (and quickly iterable) manner. From data models to ETL to databases to distributed algorithms and learning, this book has you covered.
While many resources for Java (and data science) exist, none of them combine the two, and especially not at a level where sophisticated concepts are demonstrated clearly and in simplest terms. Data Science with Java marries the two in a practical way.
Learn an extremely practical set of tools for creating enterprise grade data science applications
Get past the intimidating barrier to machine learning and statistics--and learn how useful object-oriented code can be
Автор: Slavio John Название: Statistics: Practical Concept of Statistics for Data Scientists ISBN: 1922300233 ISBN-13(EAN): 9781922300232 Издательство: Неизвестно Рейтинг: Цена: 18380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Are you trying to get started with learning statistics? This book is your answer.
Statistics are not a tool but rather a set of techniques that you have access to that will help you analyze a set of data that you either generate, receive, or give. Statistics are absolutely vital for those attempting to study big data because it allows the scientists studying the data to make sense of the information when the information is on such a large and global scale. Unlike local neighborhood statistics or marketing statistics, big data encompasses a huge range of information and often this big data will be populated by thousands if not millions of data points. Statistics help you break down these data points so that you can reasonably understand them and work with the data that comes into you.
Автор: Morrison, Faith A. Название: Uncertainty analysis for engineers and scientists ISBN: 1108745741 ISBN-13(EAN): 9781108745741 Издательство: Cambridge Academ Рейтинг: Цена: 46470.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Build the skills for determining appropriate error limits for quantities that matter with this essential toolkit. Whether you are new to the sciences or an experienced engineer, this useful text provides a practical approach to performing error analysis.
Автор: Steven Smith Название: Digital Signal Processing: A Practical Guide for Engineers and Sc ISBN: 075067444X ISBN-13(EAN): 9780750674447 Издательство: Elsevier Science Рейтинг: Цена: 87570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In addition to its thorough coverage of DSP design and programming techniques, Smith also covers the operation and usage of DSP chips. He uses Analog Devices' popular DSP chip family as design examples. Also included on the companion website is technical info on DSP processors from the four major manufacturers (Analog Devices, Texas Instruments, Motorola, and Lucent) and other DSP software. *Covers all major DSP topics *Full of insider information and shortcuts *Basic techniques and algorithms explained without complex numbers
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