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Название: Learning Data Science: Programming and Statistics Fundamentals Using Python (Sixth Early Release)
Автор: Sam Lau, Deborah Nolan, Joseph Gonzalez
Издательство: O’Reilly Media, Inc.
Год: 2023-03-23
Страниц: 434
Язык: английский
Формат: epub (true), mobi
Размер: 15.0 MB

As an aspiring data scientist, you appreciate why organizations rely on data for important decisions--whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call this the Data Science lifecycle: the process of collecting, wrangling, analyzing, and drawing conclusions from data. Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass this entire lifecycle. It's aimed at those who wish to become data scientists or who already work with data scientists, and at data analysts who wish to cross the "technical/nontechnical" divide. If you have a basic knowledge of Python programming, you'll learn how to work with data using industry-standard tools like Pandas.

Название: Python Machine Learning Projects: Learn how to build Machine Learning projects from scratch
Автор: Deepali R Vora, Gresha S Bhatia
Издательство: BPB Publications
Год: 2023
Страниц: 302
Язык: английский
Формат: pdf, epub (true)
Размер: 10.2 MB

A complete guide that will help you get familiar with Machine Learning models, algorithms, and optimization techniques. Since the last two decades, there have been many advancements in the field of Machine Learning. If you are new or want a comprehensive understanding of Machine Learning, then this book is for you. The book starts by explaining how important Machine Learning is today and the technology required to make it work. The book then helps you get familiar with basic concepts that underlie Machine Learning, including basic Python Programming. It explains different types of Machine Learning algorithms and how they can be applied in various domains like Recommendation Systems, Text Analysis and Mining, Image Processing, and Social Media Analytics. Towards the end, the book briefly introduces you to the most popular metaheuristic algorithms for optimization. By the end of the book, you will develop the skills to use Machine Learning effectively in various application domains.

Название: Mastering Python Network Automation: Automating Container Orchestration, Configuration, and Networking with Terraform, Calico, HAProxy, and Istio
Автор: Tim Peters
Издательство: GitforGits
Год: 2023
Страниц: 309
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.2 MB

With "Mastering Python Network Automation," you can streamline container orchestration, configuration management, and resilient networking with Python and its libraries, allowing you to emerge as a skilled network engineer or a strong DevOps professional. From the ground up, this guide walks readers through setting up a network automation lab using the NS3 network simulator and Python programming. This includes the installation of NS3, as well as python libraries like nornir, paramiko, netmiko, and PyEZ, as well as the configuration of ports, hosts, and servers. This book will teach you the skills to become a proficient automation developer who can test and fix any bugs in automation scripts. This book examines the emergence of the service mesh as a solution to the problems associated with service-to-service communication over time. This book walks you through automating various container-related tasks in Python and its libraries, including container orchestration, service discovery, load balancing, container storage management, container performance monitoring, and rolling updates.

Название: The Business Manager's Guide to Software Projects: A Framework for Decision-Making, Team Collaboration, and Effectiveness
Автор: Jonathan Peter Crosby
Издательство: Apress
Год: 2023
Страниц: 308
Язык: английский
Формат: pdf, epub
Размер: 12.6 MB

Every day, successful software projects scale and sustain businesses of all sizes and across all industries. Unfortunately, the reality is that many software projects still fail. The reasons behind these failures are seldom due to the underlying technology. Misunderstandings and communication barriers lead to wrong decisions, missed opportunities, communication breakdowns, or worse―huge economic loss. This book distills the world of software projects into simple terms and relatable metaphors for even the most technically adverse reader. Real-life examples, entertaining analogies, and hand-drawn illustrations will stick with readers throughout their own software projects, bolstering their success. Business requirements, use cases, process flows―the list goes on. It’s all broken down in this game-changing book aimed at delivering for business and tech teams what DevOps has done for developers and operations.

Название: Rearchitecting Software: Source Code Comprehension and Refactoring Applied to Flight Software and Simulation
Автор: Ignacio Chechile
Издательство: Independently published
Год: 2023
Страниц: 202
Язык: английский
Формат: pdf (true)
Размер: 44.7 MB

The main idea is to delve into some codebase by breaking them down and see what they are made of. We will get compiler errors galore in the process. Granted, compiler errors can be annoying, but you must embrace them, for they provide a lot of information any source code analyst must ingest and use in their own advantage. The ambitious objective of our work is to learn about two programs’ architectures and design styles in a way we will be able to alter them, refactor them, recompile them a hundred times if necessary, and eventually hook them together.For practicing code comprehension, we will use a flight simulation engine combined with a flight software framework, both running on Linux. We will fiddle with source code to make two projects that grew totally unaware of each other to interact; we will craft our tiny Frankenstein. These projects, combined together, have around 160K lines of code between C and C++ which, although not the biggest code base ever, it is still complex enough to make us think.

Название: Modeling and Simulation in Python: An Introduction for Scientists and Engineers
Автор: Allen B. Downey
Издательство: No Starch Press
Год: 2023
Страниц: 280
Язык: английский
Формат: epub (true)
Размер: 18.9 MB

Modeling and Simulation in Python is a thorough but easy-to-follow introduction to physical modeling—that is, the art of describing and simulating real-world systems. Readers are guided through modeling things like world population growth, infectious disease, bungee jumping, baseball flight trajectories, celestial mechanics, and more while simultaneously developing a strong understanding of fundamental programming concepts like loops, vectors, and functions. Clear and concise, with a focus on learning by doing, the author spares the reader abstract, theoretical complexities and gets right to hands-on examples that show how to produce useful models and simulations.

Название: Computational Statistical Methodologies and Modeling for Artificial Intelligence
Автор: Priyanka Harjule, Azizur Rahman, Basant Agarwal
Издательство: CRC Press
Серия: Edge AI in Future Computing
Год: 2023
Страниц: 389
Язык: английский
Формат: pdf (true)
Размер: 23.1 MB

This book covers computational statistics-based approaches for Artificial Intelligence (AI). The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of Data Science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. Computational statistical science is a progressive field that employs advanced computing strategies to solve and understand real-life problems. In widespread usage, computational models are integrated with Artificial Intelligence (AI) algorithms, which is the soul of the digital computer or computer-controlled robot to perform intelligent tasks. AI is an interdisciplinary field and is frequently applied to developing systems endowed with humans’ intellectual processes, including the ability to reason, identify meaning, generalize, or learn from memories. AI has multiple approaches, and advancements in Machine Learning and Deep Learning are creating a metamorphosis in every industry sector.

Название: Head First Software Architecture: A Learner's Guide to Architectural Thinking (Early Release)
Автор: Raju Gandhi, Mark Richards, Neal Ford
Издательство: O’Reilly Media, Inc.
Год: 2023-03-20
Язык: английский
Формат: epub (true)
Размер: 10.2 MB

If you're a software developer looking for a quick on-ramp to software architecture, this handy guide is a great place to start. From the authors of Fundamentals of Software Architecture, Head First Software Architecture teaches you how to think architecturally and explores the unique challenges of software architecture. You'll learn the distinction between architecture and design and the relationship between code, components, and architectural styles. You'll also learn how to work with some common architectural styles through vivid, fun examples. Quick, easy, and entertaining, this book is a valuable introduction to the world of software architecture.

Название: Frontiers of Artificial Intelligence in Medical Imaging
Автор: Navid Razmjooy, Venkatesan Rajinikanth
Издательство: IOP Publishing
Год: 2023
Страниц: 252
Язык: английский
Формат: pdf (true), epub
Размер: 76.6 MB

This book is designed to consider the recent advancements in hospitals to diagnose various diseases accurately using AI-supported detection procedures. This work examines recent AI-supported disease detection techniques from prominent researchers and clinicians working in the medical imaging processing domain. Within this book, the integration of various Artificial Intelligence (AI) methods, such as soft computing, Machine Learning, Deep Learning, and other related works will be presented. Real clinical images utilizing AI are incorporated. The book also includes several chapters on Machine Learning, convoluted neural networks, segmentation, and Deep Learning-assisted two-class and multi-class classification. Part of IOP Series in Artificial Intelligence in the Biomedical Sciences.

Название: Learning with Fractional Orthogonal Kernel Classifiers in Support Vector Machines: Theory, Algorithms and Applications
Автор: Jamal Amani Rad, Kourosh Parand, Snehashish Chakraverty
Издательство: Springer
Серия: Industrial and Applied Mathematics
Год: 2023
Страниц: 312
Язык: английский
Формат: pdf (true), epub
Размер: 42.2 MB

This book contains select chapters on support vector algorithms from different perspectives, including mathematical background, properties of various kernel functions, and several applications. The main focus of this book is on orthogonal kernel functions, and the properties of the classical kernel functions―Chebyshev, Legendre, Gegenbauer, and Jacobi―are reviewed in some chapters. Moreover, the fractional form of these kernel functions is introduced in the same chapters, and for ease of use for these kernel functions, a tutorial on a Python package named ORSVM is presented. The book also exhibits a variety of applications for support vector algorithms, and in addition to the classification, these algorithms along with the introduced kernel functions are utilized for solving ordinary, partial, integro, and fractional differential equations. On the other hand, nowadays, the real-time and big data applications of support vector algorithms are growing. Consequently, the Compute Unified Device Architecture (CUDA) parallelizing the procedure of support vector algorithms based on orthogonal kernel functions is presented. The book sheds light on how to use support vector algorithms based on orthogonal kernel functions in different situations and gives a significant perspective to all Machine Learning and scientific Machine Learning researchers all around the world to utilize fractional orthogonal kernel functions in their pattern recognition or scientific computing problems.