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Название: Measurements and Data Analysis for Agricultural Engineers Using Python
Автор: Matti Pastell
Издательство: Leanpub
Год: March 1, 2016
Страниц: 131
Язык: английский
Формат: pdf (true), epub
Размер: 10.2 MB

This book is based on my lecture notes from the course “Measurement technology” at my previous position in the Department of Agricultural Sciences at the University of Helsinki. The book has two parts: The beginning covers the basics of the theory needed to understand proper sampling and planning of measurement systems. It also covers basics of data loggers and sensor connections. The book doesn’t cover sensor, this information is difficult to keep up to date and there are several books focusing on sensors already. The second part covers the basics of Python, Scientific Python with applications to spectral analysis and digital filtering. The focus is on examples in signal processing. The reason I chose Python for my teaching was that I wanted to have one language that can be used to write software for data collection, interface hardware and analyze data. I also wanted to have a language that is easy to learn, free for students to use for homework and on their own projects and works on multiple operating systems. In addition to Python being popular general purpose A lot of dataloggers have drivers for Python, the SciPy stack is a powerful option for scientific computing and OpenCV Python interface allows the implementation of popular computer vision applications.

Название: Stroke: Analysis and Prediction Using Scikit-Learn, Keras, and TensorFlow with Python GUI, Second Edition
Автор: Vivian Siahaan, Rismon Sianipar
Издательство: Balige Publishing
Год: July 2023
Страниц: 525
Язык: английский
Формат: epub (true)
Размер: 18.4 MB

In this project, we will perform an analysis and prediction task on stroke data using Machine Learning and deep learning techniques. The entire process will be implemented with Python GUI for a user-friendly experience. We start by exploring the stroke dataset, which contains information about various factors related to individuals and their likelihood of experiencing a stroke. We load the dataset and examine its structure, features, and statistical summary. Next, we preprocess the data to ensure its suitability for training machine learning models. This involves handling missing values, encoding categorical variables, and scaling numerical features. We utilize techniques such as data imputation and label encoding. To gain insights from the data, we visualize its distribution and relationships between variables. We create plots such as histograms, scatter plots, and correlation matrices to understand the patterns and correlations in the data. To improve model performance and reduce dimensionality, we select the most relevant features for prediction. We employ techniques such as correlation analysis, feature importance ranking, and domain knowledge to identify the key predictors of stroke. With the models trained and saved, we move on to implementing the Python GUI. We utilize PyQt libraries to create an interactive graphical user interface that provides a seamless user experience. The GUI consists of various components such as buttons, checkboxes, input fields, and plots. These components allow users to interact with the application, select prediction models, and visualize the results.

Название: The Dynamic Programming Manual: Mastering Efficient Solutions
Автор: Gabor Laszlo Hajba
Издательство: Leanpub
Год: 2023-06-30
Страниц: 220
Язык: английский
Формат: pdf (true), mobi, epub
Размер: 10.1 MB

Unleash the power of dynamic programming! Master efficiency and solve complex problems with expertly crafted solutions. Java and Python code examples guide your path to optimized application performance. Dive into "The Dynamic Programming Manual" and unlock the secrets of success! Welcome to "The Dynamic Programming Manual: Mastering Efficient Solutions." This book is your comprehensive guide to mastering dynamic programming techniques through a collection of engaging exercises and their efficient solutions, accompanied by detailed explanations of how to approach similar problems. Are you passionate about algorithms? Do you want to conquer challenges that become sluggish with increasing input using brute force techniques? Whether you code in Java or Python, this book will spark your creativity and provide valuable insights to enhance your code. Even if you work with a different programming language, fear not! The principles of programming are universal, and the examples in this book will help you grasp the essence of dynamic programming easily.

Название: Python for History Buffs
Автор: Andrew Kean Gao
Издательство: Leanpub
Год: 2023-07-16
Язык: английский
Формат: pdf (true), epub
Размер: 11.1 MB

Coding is a valuable skill for historians and scholars of the humanities. Learn Python, one of the easiest and most versatile programming languages, from the ground up. Welcome to “Python for History Buffs”! This book is designed to take you on a journey through time, exploring the fascinating world of history while simultaneously learning the basics of Python programming. Programming is a skill that has become increasingly important in our modern world. It’s a tool that allows us to create software, analyze data, build websites, and much more. Python, in particular, is a powerful, versatile language that’s great for beginners due to its readability and simplicity. History, on the other hand, is the study of our past. It helps us understand where we come from and how past events and people have shaped the world we live in today. By studying history, we can learn valuable lessons and gain a broader perspective on life. In this book, we’ll be combining these two seemingly disparate subjects. As we journey through different historical periods, we’ll be learning corresponding Python concepts. For example, as we explore the dawn of civilization, we’ll also be learning the basics of Python. As we delve into the Industrial Revolution, we’ll learn about file input/output in Python, mirroring the era’s focus on efficiency and productivity. Each chapter of this book will focus on a specific historical period and a corresponding Python concept. We’ll start with the basics and gradually move on to more advanced topics.

Название: Programming for Kids: Learn Programming by Following Along in Ruby on a Mac
Автор: Peter Armstrong
Издательство: Leanpub
Год: 2022-04-14
Страниц: 137
Язык: английский
Формат: pdf (true), epub
Размер: 10.2 MB

This book teaches kids between 10 and 14 years old the basics of programming. You need a Mac computer to follow along with the examples. The examples use Terminal, nano, Ruby and irb. (Yes, I'm serious!) This book will teach you how to write computer programs! You will need to use a Mac computer to follow along. The programs are short, so you can type them all in yourself. This is true even if you can’t type well. This book has a bunch of small chapters. Each chapter is about one idea. At the end of every chapter, there will be exercises for you to do. It is really important that you do all of them! Doing the exercises ensures that you know the material in the chapter. The answers for all the exercises are in the back of the book, and there are links to the answers for all the exercises. If your parents want to find out more about this book, they can read it with you. Or, they can just read the For Parents section at the back of the book. If you’re going to use their computer, they might want to sit with you. That’s fine. They’ll learn something too! Ruby is a programming language. You speak English, but there are lots of other languages that people speak. Similarly, there are lots of different languages you can use to tell a computer what to do. Ruby is one of the easier ones to use, and your Mac comes with Ruby already installed. The program you wrote was a Ruby program!

Название: Практический Machine Learning
Автор: Stepik
Издательство: Интернет-издание
Год: 2023
Формат: PDF
Страниц: 319
Размер: 35 Mb
Язык: Русский

В курсе изучаются классические и продвинутые алгоритмы машинного обучения, подробно разбираются математические обоснования изучаемых методов. После прохождения курса вы сможете полностью решать классические задачи анализа данных: начиная от сбора и хранения данных и заканчивая внедрением обученных моделей в продакшн. Курс предназначен для тех, кто интересуется машинном обучением в его современном состоянии, а также не хочет ограничиваться только анализом данных.

Название: Основы алгоритмизации и программирования на языке Microsoft Visual Basic
Автор(ы): Гуриков С.Р.
Издательство: Инфра-М
Год: 2022
Страниц: 595
Формат: PDF
Размер: 111 Мб
Язык: русский

В учебном пособии рассматриваются основы алгоритмизации и программирования на языке Microsoft Visual Basic. Содержит описание такого традиционного материала, необходимого для изучения основ алгоритмизации, как работа линейных, разветвляющихся и циклических структур, обработка одномерных и двумерных массивов, программирование с использованием функций и процедур, обработка строк и т.д. Обсуждаются типы данных, используемые в VB, сделан обзор основных элементов управления среды программирования, уделено внимание методам ввода и вывода данных. Также изложены вопросы работы с графикой на основе использования интерфейса GDI+.

Название: Visual Basic для студентов и школьников (+CD-ROM)
Автор: Культин Н.Б., Цой Л.Б.
Издательство: БХВ-Петербург
Год: 2010
Страниц: 405
ISBN: 978-5-9775-0487-4
Формат: PDF
Размер: 104 Мб
Язык: русский
Серия: ИиИКТ

Рассматривается процесс создания программ различного назначения на языке программирования Visual Basic - от простейших до программ работы с графикой и базами данных. Последовательность изложения, дозировка материала, а также наличие контрольных вопросов и задач для решения соотносятся с учебным процессом.

Название: Программирование на Python в примерах и задачах
Автор(ы): Васильев Алексей
Издательство: Эксмо
Год: 2022
Страниц: 618
Формат: PDF
Размер: 20 Мб
Язык: русский

Сегодня существует много разных языков программирования. Некоторые из них популярны, а некоторые — не очень. Обычно популярность языка определяют по количеству программистов, которые используют его в своей работе на постоянной основе, или по запросам работодателей, которые ищут сотрудников-программистов. Долгие годы традиционно популярными являются языки программирования Java, C++, C#, jаvascript и PHP. В последнее время в этой великолепной компании все чаще упоминается язык программирования Python. Даже больше — по некоторым опросам язык Python уже занимает лидирующие позиции. Именно этому языку посвящена книга.

Название: Machine Learning for Civil and Environmental Engineers: A Practical Approach to Data-driven Analysis, Explainability, and Causality
Автор: M. Z. Naser
Издательство: Wiley
Год: 2023
Страниц: 610
Язык: английский
Формат: pdf (true)
Размер: 39.5 MB

Accessible and practical framework for machine learning applications and solutions for civil and environmental engineers This textbook introduces engineers and engineering students to the applications of Artificial Intelligence (AI), Machine Learning (ML), and machine intelligence (MI) in relation to civil and environmental engineering projects and problems, presenting state-of-the-art methodologies and techniques to develop and implement algorithms in the engineering domain. Through real-world projects like analysis and design of structural members, optimizing concrete mixtures for site applications, examining concrete cracking via computer vision, evaluating the response of bridges to hazards, and predicating water quality and energy expenditure in buildings, this textbook offers readers in-depth case studies with solved problems that are commonly faced by civil and environmental engineers. The approaches presented range from simplified to advanced methods, incorporating coding-based and coding-free techniques. Professional engineers and engineering students will find value in the step-by-step examples that are accompanied by sample databases and codes for readers to practice with. In general, there are three types of learning that ML can fall under; supervised learning, unsupervised learning, and semi-supervised learning. This textbook is a must-have reference for undergraduate/graduate students to learn concepts on the use of Machine Learning, for scientists/researchers to learn how to integrate Machine Learning into civil and environmental engineering, and for design/engineering professionals as a reference guide for undertaking MI design, simulation, and optimization for infrastructure.