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Название: Feature Selection in Machine Learning with Feature-engine: Discover feature selection algorithms that scale well and overcome the limitations of statistical models or the computational cost of wrapper methods
Автор: Soledad Galli, PhD
Издательство: Leanpub
Год: 2022-08-24
Язык: английский
Формат: pdf (true), epub
Размер: 14.7 MB

Learn how to implement various feature selection methods in a few lines of code utilizing the open-source Python library Feature-engine. Feature-engine is an open-source Python library for feature engineering and feature selection. It uses Pandas and Scikit-learn under the hood to engineer and select feature subsets. Feature selection is the process of selecting a subset of features from the total variables in a data set to train machine learning algorithms. Feature selection is key for developing simpler, faster, and highly performant machine learning models. The aim of any feature selection algorithm is to create classifiers or regression models that run faster and whose outputs are easier to understand by their users. We will use the Python libraries Matplotlib, NumPy, Pandas, Scikit-learn and Feature-engine.

Название: Программируем на Java, 5-е межд. изд.
Автор: Лой Марк, Нимайер Патрик, Лук Дэниэл
Издательство: Питер
Год: 2023
Формат: pdf
Страниц: 544
Размер: 18,5 Мб
Язык: русский

Неважно, кто вы – разработчик ПО или пользователь, в любом случае вы слышали о языке Java. В этой книге вы на конкретных примерах изучите основы Java, API, библиотеки классов, приемы и идиомы программирования. Особое внимание авторы уделяют построению реальных приложений.
Вы освоите средства управления ресурсами и исключениями, а также познакомитесь с новыми возможностями языка, появившимися в последних версиях Java.
• Программируйте на Java с использованием компилятора, интерпретатора и других инструментов.
• Исследуйте средства управления потоками и параллельной обработки.
• Изучайте обработку текста и мощные API.
• Создавайте приложения и службы на базе современных сетевых коммуникаций или веб-технологий.

Название: MATLAB Automated Driving Toolbox User’s Guide (R2022b)
Автор: MathWorks
Издательство: The MathWorks, Inc.
Год: September 2022
Страниц: 2060
Язык: английский
Формат: pdf (true)
Размер: 60.3 MB

Automated Driving Toolbox provides algorithms and tools for designing, simulating, and testing ADAS and autonomous driving systems. You can design and test vision and lidar perception systems, as well as sensor fusion, path planning, and vehicle controllers. Visualization tools include a bird’s-eye-view plot and scope for sensor coverage, detections and tracks, and displays for video, lidar, and maps. The toolbox lets you import and work with HERE HD Live Map data and OpenDRIVE road networks. Using the Ground Truth Labeler app, you can automate the labeling of ground truth to train and evaluate perception algorithms. For hardware-in-the-loop (HIL) testing and desktop simulation of perception, sensor fusion, path planning, and control logic, you can generate and simulate driving scenarios.

Название: MATLAB & Simulink Vehicle Network Toolbox User’s Guide (R2022b)
Автор: MathWorks
Издательство: The MathWorks, Inc.
Год: September 2022
Страниц: 854
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Vehicle Network Toolbox provides MATLAB® functions and Simulink blocks for sending, receiving, encoding, and decoding CAN, CAN FD, J1939, and XCP messages. The toolbox lets you identify and parse specific signals using industry-standard CAN database files and then visualize the decoded signals using the CAN Explorer and CAN FD Explorer apps. Using A2L description files, you can connect to an ECU via XCP on CAN or Ethernet. You can access messages and measurement data stored in MDF files. The toolbox simplifies communication with in-vehicle networks and lets you monitor, filter, and analyze live CAN bus data or log and record messages for later analysis and replay.

Название: Time Series Algorithms Recipes: Implement Machine Learning and Deep Learning Techniques with Python
Автор: Akshay R Kulkarni, Adarsha Shivananda, Anoosh Kulkarni, V Adithya Krishnan
Издательство: Apress
Год: 2023
Страниц: 188
Язык: английский
Формат: pdf (true), epub
Размер: 15.4 MB

This book teaches the practical implementation of various concepts for time series analysis and modeling with Python through problem-solution-style recipes, starting with data reading and preprocessing. It begins with the fundamentals of time series forecasting using statistical modeling methods like AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average), and ARIMA (autoregressive integrated moving-average). Next, you'll learn univariate and multivariate modeling using different open-sourced packages like Fbprohet, stats model, and sklearn. You'll also gain insight into classic machine learning-based regression models like randomForest, Xgboost, and LightGBM for forecasting problems. The book concludes by demonstrating the implementation of Deep Learning models (LSTMs and ANN) for time series forecasting. Each chapter includes several code examples and illustrations.

Название: Exploring Game Mechanics: Principles and Techniques to Make Fun, Engaging Games
Автор: Maithili Dhule
Издательство: Apress
Год: 2022
Страниц: 205
Язык: английский
Формат: pdf (true), epub
Размер: 29.9 MB

Learn simple yet powerful, modern-day techniques used in various gaming genres, including casual and puzzle, strategy and simulation, action-adventure, and role-playing. This book is your pocket-sized guide to designing interesting and engaging mechanics for any type of game. Exploring Game Mechanics is a cornucopia of concepts related to gameplay mechanics that you can use to create games that are fun and rewarding to play. Dive into key gameplay elements that improve the player experience, such as implementing in-game tutorials, controlling the flow of player-choice-based games, and building a game narrative through storytelling. Understand how to establish the game’s end goal for the player to work towards by creating quests, missions, and objectives.

Название: Go Mini Reference: A Quick Guide to the Go Programming Language for Busy Coders
Автор: Harry Yoon
Издательство: Coding Books Press
Год: September 2022
Страниц: 184
Язык: английский
Формат: pdf, mobi, epub
Размер: 10.1 MB

Learn Golang Essentials in a Weekend!Go is one of the most powerful, and yet the simplest, modern programming languages. We go through all important features of the modern Go programming language (as of 1.18 and 1.19 - 2022), including generics! The Go programming language differentiates itself with a set of unique features, including the builtin concurrency support via goroutines. But, more importantly, Go stands out, among these hundreds of modern languages, in terms of its fundamental language design philosophy. First of all, Go is a "minimalistic" language. Go is reminiscent of simple languages like Lua. The similarity between Go and Lua goes far deeper than their syntactic appearances. The minimalism is at the heart of the Go programming language design. Second, Go values the stability of the language over anything else. This is in contrast with many other programming languages which are literally in the "arms race" for more and more features. Go is more like the C programming language in this regards, which has gone through absolutely minimal changes since its creation over four decades ago.

Название: Python for Serious Beginners 2022: A Practical Introduction to Modern Python with Simple Hands-on Projects
Автор: Harry Yoon
Издательство: Coding Books Press
Год: 2022-09-07 (Revision 1.6.2)
Страниц: 318
Язык: английский
Формат: pdf, mobi, epub
Размер: 10.1 MB

Learn Real Python Programming Today! With Hands-On Coding Projects and Exercises. Wanna learn programming? Wanna learn Python? Start from this book! This book will teach you the fundamentals of programming and the Python language basics, in a series of thoughtfully organized lessons for the most effective learning experience. It includes many hands-on exercises! Python for Serious Beginners will give you the best introduction to programming in Python whether you are coming from a different programming language background or you are learning programming for the first time. This book covers all the essential features of Modern Python (Python 3.10/3.11) through the carefully designed code examples.

Название: Probabilistic Machine Learning for Finance and Investing: A Primer to the Next Generation of AI with Python (Third Early Release)
Автор: Deepak Kanungo
Издательство: O’Reilly Media, Inc.
Год: 2022-12-21
Страниц: 143
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.2 MB

Whether based on academic theories or machine learning strategies, all financial models are at the mercy of modeling errors that can be mitigated but not eliminated. Probabilistic ML technologies are based on a simple and intuitive definition of probability and the rigorous calculus of probability theory. These systems treat uncertainties and errors of financial and investing systems as features, not bugs. And they quantify uncertainty generated from inexact inputs and outputs as probability distributions, not point estimates. This makes for realistic financial inferences and predictions that are useful for decision-making and risk management. These systems are capable of warning us when their inferences and predictions are no longer useful in the current market environment.

Название: Concise Guide to Quantum Machine Learning
Автор: Davide Pastorello
Издательство: Springer
Серия: Machine Learning: Foundations, Methodologies, and Applications
Год: 2023
Страниц: 144
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

This book offers a brief but effective introduction to Quantum Machine Learning (QML). QML is not merely a translation of classical machine learning techniques into the language of quantum computing, but rather a new approach to data representation and processing. Accordingly, the content is not divided into a “classical part” that describes standard machine learning schemes and a “quantum part” that addresses their quantum counterparts. Instead, to immerse the reader in the quantum realm from the outset, the book starts from fundamental notions of quantum mechanics and quantum computing. Avoiding unnecessary details, it presents the concepts and mathematical tools that are essential for the required quantum formalism. In turn, it reviews those quantum algorithms most relevant to Machine Learning. Later chapters highlight the latest advances in this field and discuss the most promising directions for future research.