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The goal of this book is to reduce the complexity and clarify the abstractions with concrete visual examples driven by simple python programs.
This advanced undergraduate textbook presents a new approach to teaching mathematical methods for scientists and engineers. It provides a practical, pedagogical introduction to utilizing Python in Mathematical and Computational Methods courses.
A friendly, fully-illustrated introduction to the most important computer programming algorithms. Suitable for self-taught programmers, engineers, job seekers, or anyone who wants to brush up on algorithms.
The core aim of the book is to provide a self-contained introduction to R (both Base R and the tidyverse) and show how this knowledge can be applied to a range of OR... Læs mere
Focused on various forms of time-to-event data methodologies, this book helps readers master the application of Bayesian mediation analysis using R. Across ten... Læs mere
This book introduces algorithmic approaches to computational design through both Grasshopper and Python. This book (including its accompanying code and... Læs mere
This concise volume, using examples of psychotherapy talk, showcases the potential applications of data analytics for advancing discourse research and other related disciplines.
This book provides an accessible introduction to intermediate-level electrodynamics with computational approaches to complement a traditional mathematical treatment of the subject.
The intention is to guide the reader through the R landscape of 2023 and beyond. The second edition contains 24 new diagrams and flowcharts, seven new tables, and revised text and code examples for clarity.
This book focuses on the hands-on approach to learning Data Mining. It showcases how to use Python Packages to fulfill the Data Mining pipeline, which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge.
Software Design by Example: A Tool-Based Introduction with Python builds small versions of the things programmers use in order to give... Læs mere
This book illustrates statistics with the R programming language, an emerging tool in data science. Filled with techniques for data science and analytics programming, the book is written for students and professionals. It is focused on learning outcomes and problem solving.