Название: Machine Learning for Neuroscience: A Systematic Approach
Автор: Chuck Easttom
Издательство: CRC Press
Год: 2024
Страниц: 305
Язык: английский
Формат: pdf (true)
Размер: 16.8 MB

This book addresses the growing need for Machine Learning and data mining in neuroscience. The book offers a basic overview of the neuroscience, Machine Learning and the required math and programming necessary to develop reliable working models. The material is presented in a easy to follow user-friendly manner and is replete with fully working Machine Learning code. Machine Learning for Neuroscience: A Systematic Approach, tackles the needs of neuroscience researchers and practitioners that have very little training relevant to Machine Learning. The first section of the book provides an overview of necessary topics in order to delve into Machine Learning, including basic linear algebra and Python programming. The second section provides an overview of neuroscience and is directed to the Computer Science oriented readers. You are going to work a lot with TensorFlow later in this book. Much of the use of TensorFlow will make more sense once you have read the chapters regarding Machine Learning.

Название: Using Julia for Introductory Econometrics
Автор: Florian Heiss, Daniel Brunner
Издательство: UPfIE
Год: 2023
Страниц: 402
Язык: английский
Формат: pdf (true)
Размер: 11.7 MB

Introduces the popular, powerful and free programming language and software package Julia. Julia an ideal candidate for starting to learn econometrics and data analysis. As we will show in this book, learning Julia and the basics of econometrics are two goals that can be achieved very well together. And Julia is completely free and available for all relevant operating systems. When using it in econometrics courses, students can easily download a copy to their own computers and use it at home (or their favorite cafés) to replicate examples and work on take-home assignments. This hands-on experience is essential for the understanding of the econometric models and methods. It also prepares students to conduct their own empirical analyses for their theses, research projects, and professional work.

Название: Using Python for Introductory Econometrics
Автор: Florian Heiss, Daniel Brunner
Издательство: UPfIE
Год: 2020
Страниц: 428
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Introduces the popular, powerful and free programming language and software package Python. Python is an ideal candidate for starting to learn econometrics and data analysis. It has a huge user base, especially in the fields of data science, machine learning, and artificial intelligence, where it arguably is the most popular software overall. These are very exciting areas and there is a lot of cutting edge research in the integration of their tools into the econometrics toolbox. So why not kill two birds with one stone and master a powerful and important software package while learning econometrics at the same time? Because Python must be hard to learn and to apply to econometrics? It is not at all, as this book shows. And Python is completely free and available for all relevant operating systems. When using it in econometrics courses, students can easily download a copy to their own computers and use it at home (or their favorite cafés) to replicate examples and work on take-home assignments. This hands-on experience is essential for the understanding of the econometric models and methods. It also prepares students to conduct their own empirical analyses for their theses, research projects, and professional work.

Название: Essential F#: Succinct, Robust, Performan
Автор: Ian Russell
Издательство: Leanpub
Год: 2023-01-30
Страниц: 207
Язык: английский
Формат: pdf (true), epub, mobi
Размер: 10.2 MB

This is a practical book aimed at efficiently getting you up to speed with the essentials of functional-first programming in F#. It will help you to discover why F# is such a popular language with those who have spent time learning its secrets. This book is targeted at folks wanting to learn F# and assumes that the reader has no real knowledge of F# or functional programming. Some programming experience, particularly in C# or VB.NET, may be useful but not absolutely necessary. Although F# has often been portrayed as a functional programming language, it isn’t, and neither is this book purely about functional programming. You are not going to learn about Category Theory, Lambda Calculus, or even Monads. You will learn things about programming in a functional-first style as a by-product of how we solve problems with F#. What you will learn is how F#’s functional-first approach to programming empowers everyone to write succinct, robust, and performant code. You will learn a lot of new terminology as you read this book but only enough to understand the features of F# that allow us to solve real-world problems with clearly expressed and concise code.

Название: Intelligence-Driven Incident Response: Outwitting the Adversary 2nd Edition (Final)
Автор: Rebekah Brown, Scott J. Roberts
Издательство: O’Reilly Media, Inc.
Год: 2023
Страниц: 480
Язык: английский
Формат: pdf, epub
Размер: 10.2 MB

Cyber-threat intelligence isn’t a new concept, simply a new name for an old approach: applying a structured analytical process to understand an attack and the adversary behind it. The application of threat intelligence to network security is more recent, but the basics haven’t changed. Cyber-threat intelligence involves applying intelligence processes and concepts—some of the oldest concepts that exist—and making them a part of the overall information security process. Threat intelligence has many applications, but one of the fundamental ways it can be utilized is as an integral part of the intrusion-detection and incident-response process. We call this intelligence-driven incident response and think it is something every security team can do, with or without a major capital investment. It’s less about tools, although they certainly help sometimes, and more about a shift in the way we approach the incident-response process. Intelligence-driven incident response will help not only to identify, understand, and eradicate threats within a network, but also to strengthen the entire information security process to improve those responses in the future.

Название: Building Cross-Platform Apps with Flutter and Dart: Build scalable apps for Android, iOS, and web from a single codebase
Автор: Deven Joshi
Издательство: BPB Publications
Год: 2023
Страниц: 446
Язык: английский
Формат: epub
Размер: 73.2 MB

Learn how to create powerful apps for multiple platforms with Flutter and Dart. Flutter and Dart have emerged as a powerful duo that empowers developers to create stunning and feature-rich apps for Android, iOS, and web platforms from a single codebase. By leveraging Flutter's rich set of customizable widgets and Dart's reactive programming model, you can create visually appealing and interactive user interfaces that feel native on both iOS and Android devices. This book adopts a hands-on approach to help you progress from fundamental to advanced concepts in Flutter development, establishing a solid foundation along the way. It will teach you how to create elegant user interfaces, utilize Flutter's Widget library, and incorporate captivating animations for enhanced user experience. It will also guide you through building apps that work seamlessly on all supported Flutter platforms, saving you time and effort.

Название: ООП в языке Java. Сборник заданий и тематических примеров
Автор: Кравчук А.С., Кравчук А.И., Кремень Е.В.
Издательство: Минск: БГУ
Год: 2023
Формат: pdf
Страниц: 150
Размер: 13 mb
Язык: русский

Сборник заданий предназначен для проработки приемов объектно-ориентированного программирования в языке Java. Издание содержит задачи на обработку массивов, реализацию интерфейсов, наследование, использование коллекций, дженериков и лямбда-выражений. В каждой теме приводятся примеры решения типовых задач и варианты индивидуальные заданий. Издание ориентировано в первую очередь на тех, кто не имеет опыта практического программирования на языке Java и адресуется студентам, а также всем, кто хотел бы научиться приемам программирования стандартных задач.

Название: Язык C++. Императивное программирование
Автор: Кравчук А.С., Кравчук А.И., Кремень Е.В.
Издательство: Минск: БГУ
Год: 2023
Формат: pdf
Страниц: 389
Размер: 20 mb
Язык: русский

Издание ориентировано на развитие и закрепление у студентов профессиональных навыков использования императивного программирования, как одного из основных инструментов решения прикладных задач. Это объясняется тем, что студент обязан хорошо освоить методологию использования функций, прежде чем он начнет понимать, как используются методы при создании и работе с объектами классов. В пособие включен такой методический материал, как таблицы ручного счета простейших алгоритмов, так и сопоставление кода простейших программ на С++ и Pascal.
Издание адресуется прежде всего студентам, а также всем, кто хотел бы научиться приемам программирования при решении стандартных задач.

Название: Robot Souls: Programming in Humanity
Автор: Eve Poole
Издательство: CRC Press
Год: 2024
Страниц: 185
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Two of the biggest design problems in Artificial Intelligence are how to build robots that behave in line with human values and how to stop them ever going rogue. One under-explored solution to these alignment and control problems might be to examine how these are already addressed in the design of humans. Looking closely at the human blueprint, it contains a suite of capacities that are so clumsy they have generally been kept away from AI. It was assumed that robots with features like emotions and intuition, that made mistakes and looked for meaning and purpose, would not work as well as robots without this kind of code. But on considering why all these irrational properties are there, it seems that they emerge from the source code of soul. Because it is actually this ‘junk’ code that makes us human and promotes the kind of reciprocal altruism that keeps humanity alive and thriving. Machine Learning is the general term for the development of algorithms in AI that drive its autonomous development, using training data to enable the AI to make future predictions or decisions without being explicitly programmed to do so. Deep Learning has now taken this to a level of complexity that has produced a step-change in the progress of AI.

Название: Artificial Intelligence For Science: A Deep Learning Revolution
Автор: Alok Choudhary, Geoffrey Fox, Tony Hey
Издательство: World Scientific Publishing
Год: 2023
Страниц: 803
Язык: английский
Формат: pdf (true)
Размер: 172.5 MB

This unique collection introduces AI, Machine Learning (ML), and deep neural network technologies leading to scientific discovery from the datasets generated both by supercomputer simulation and by modern experimental facilities. To work with Deep Learning methods, practitioners rely on Deep Learning frameworks — a specialized software which allows users to design and train Artificial Neural Networks (ANNs). Popular titles include PyTorch, TensorFlow, and MXNet among others. In summary, the frameworks allow users to (a) construct an ANN from basic tensor operations and a predefined set of basic building blocks (convolutional kernels, dense layers, recurrent units, various activation functions, etc.), (b) compute derivatives of the loss function for back-propagation, (c) execute forward and backward passes efficiently on a given hardware, and (d) provide additional helper functions for distributed training, data handling, etc.