Tag: Chapman

Free Download Bayesian Modeling and Computation in Python (Chapman & Hall/CRC Texts in Statistical Science) by Osvaldo A. Martin, Ravin Kumar, Junpeng Lao
English | December 29, 2021 | ISBN: 036789436X | 398 pages | MOBI | 29 Mb
Bayesian Modeling and Computation in Python aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands on approach with PyMC3, Tensorflow Probability, ArviZ and other libraries focusing on the practice of applied statistics with references to the underlying mathematical theory.

Free Download Artificial Intelligence and Causal Inference (Chapman & Hall/CRC Machine Learning & Pattern Recognition) by Momiao Xiong
English | March 8, 2022 | ISBN: 0367859408 | 394 pages | MOBI | 4.83 Mb
Artificial Intelligence and Causal Inference address the recent development of relationships between artificial intelligence (AI) and causal inference. Despite significant progress in AI, a great challenge in AI development we are still facing is to understand mechanism underlying intelligence, including reasoning, planning and imagination. Understanding, transfer and generalization are major principles that give rise intelligence. One of a key component for understanding is causal inference. Causal inference includes intervention, domain shift learning, temporal structure and counterfactual thinking as major concepts to understand causation and reasoning. Unfortunately, these essential components of the causality are often overlooked by machine learning, which leads to some failure of the deep learning. AI and causal inference involve (1) using AI techniques as major tools for causal analysis and (2) applying the causal concepts and causal analysis methods to solving AI problems. The purpose of this book is to fill the gap between the AI and modern causal analysis for further facilitating the AI revolution. This book is ideal for graduate students and researchers in AI, data science, causal inference, statistics, genomics, bioinformatics and precision medicine.

Free Download Mathematical Engineering of Deep Learning (Chapman & Hall/CRC Data Science Series) by Benoit Liquet, Sarat Moka, Yoni Nazarathy
English | October 3, 2024 | ISBN: 1032288280 | 414 pages | MOBI | 12 Mb
Mathematical Engineering of Deep Learning provides a complete and concise overview of deep learning using the language of mathematics. The book provides a self-contained background on machine learning and optimization algorithms and progresses through the key ideas of deep learning. These ideas and architectures include deep neural networks, convolutional models, recurrent models, long/short-term memory, the attention mechanism, transformers, variational auto-encoders, diffusion models, generative adversarial networks, reinforcement learning, and graph neural networks. Concepts are presented using simple mathematical equations together with a concise description of relevant tricks of the trade. The content is the foundation for state-of-the-art artificial intelligence applications, involving images, sound, large language models, and other domains. The focus is on the basic mathematical description of algorithms and methods and does not require computer programming. The presentation is also agnostic to neuroscientific relationships, historical perspectives, and theoretical research. The benefit of such a concise approach is that a mathematically equipped reader can quickly grasp the essence of deep learning.

Free Download Python Packages (Chapman & Hall/CRC The Python Series) by Tomas Beuzen, Tiffany Timbers
English | April 21, 2022 | ISBN: 1032029447 | 222 pages | EPUB | 18 Mb
Python Packages introduces Python packaging at an introductory and practical level that’s suitable for those with no previous packaging experience. Despite this, the text builds up to advanced topics such as automated testing, creating documentation, versioning and updating a package, and implementing continuous integration and deployment. Covering the entire Python packaging life cycle, this essential guide takes readers from package creation all the way to effective maintenance and updating.

Free Download Practitioner’s Guide to Data Science (Chapman & Hall/CRC Data Science Series) by Hui Lin, Ming Li
English | May 24, 2023 | ISBN: 0815354398 | 402 pages | EPUB | 21 Mb
This book aims to increase the visibility of data science in real-world, which differs from what you learn from a typical textbook. Many aspects of day-to-day data science work are almost absent from conventional statistics, machine learning, and data science curriculum. Yet these activities account for a considerable share of the time and effort for data professionals in the industry. Based on industry experience, this book outlines real-world scenarios and discusses pitfalls that data science practitioners should avoid. It also covers the big data cloud platform and the art of data science, such as soft skills. The authors use R as the primary tool and provide code for both R and Python.

Free Download Introduction to Python for Humanists (Chapman & Hall/CRC The Python Series) by William Mattingly
English | July 26, 2023 | ISBN: 1032378379 | 362 pages | PDF | 34 Mb
This book will introduce digital humanists at all levels of education to Python. It provides background and guidance on learning the Python computer programming language, and as it presumes no knowledge on the part of the reader about computers or coding concepts allows the reader to gradually learn the more complex tasks that are currently popular in the field of digital humanities. This book will be aimed at undergraduates, graduates, and faculty who are interested in learning how to use Python as a tool within their workflow. An Introduction to Python for Digital Humanists will act as a primer for students who wish to use Python, allowing them to engage with more advanced textbooks. This book fills a real need, as it is first Python introduction to be aimed squarely at humanities students, as other books currently available do not approach Python from a humanities perspective. It will be designed so that those experienced in Python can teach from it, in addition to allowing those who are interested in being self-taught can use it for that purpose.

Free Download Data Science (Chapman & Hall/CRC Data Science Series) by Tiffany Timbers, Trevor Campbell, Melissa Lee
English | August 22, 2024 | ISBN: 103257223X | 452 pages | MOBI | 23 Mb
Data Science: A First Introduction with Python focuses on using the Python programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, regression, clustering, and inference. It emphasizes workflows that are clear, reproducible, and shareable, and includes coverage of the basics of version control. Based on educational research and active learning principles, the book uses a modern approach to Python and includes accompanying autograded Jupyter worksheets for interactive, self-directed learning. The text will leave readers well-prepared for data science projects. It is designed for learners from all disciplines with minimal prior knowledge of mathematics and programming. The authors have honed the material through years of experience teaching thousands of undergraduates at the University of British Columbia.

Free Download A Simple Introduction to Python (Chapman & Hall/CRC The Python Series) by Stephen Lynch
English | June 11, 2024 | ISBN: 1032750294 | 92 pages | MOBI | 5.71 Mb
A Simple Introduction to Python is aimed at pre-university students and complete novices to programming. The whole book has been created using Jupyter notebooks. After introducing Python as a powerful calculator, simple programming constructs are covered, and the NumPy, MatDescriptionLib and SymPy modules (libraries) are introduced. Python is then used for Mathematics, Cryptography, Artificial Intelligence, Data Science and Object Oriented Programming.

Free Download Tidy Finance with Python (Chapman & Hall/CRC The Python Series) by Christoph Scheuch, Stefan Voigt, Christoph Frey
English | June 22, 2024 | ISBN: 1032676418 | 262 pages | MOBI | 3.90 Mb
This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using pandas, numpy, and Descriptionnine. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques.

Free Download Introduction to Python (Chapman & Hall/CRC The Python Series) by David Báez-López, David Alfredo Báez Villegas
English | July 2, 2024 | ISBN: 1032119101 | 452 pages | MOBI | 8.00 Mb
Introduction to Python: with Applications in Optimization, Image and Video Processing, and Machine Learning is intended primarily for advanced undergraduate and graduate students in quantitative sciences such as mathematics, computer science, and engineering. In addition to this, the book is written in such a way that it can also serve as a self-contained handbook for professionals working in quantitative fields including finance, IT, and many other industries where programming is a useful or essential tool.