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Thoughtful Machine Learning with Python
Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext. Featuring graphs and highlighted code examples throughout, the book features tests with Python's Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If you're a software engineer or business analyst interested in data science, this book will help you: Reference real-world examples to test each algorithm through engaging, hands-on exercises Apply test-driven development (TDD) to write and run tests before you start coding Explore techniques for improving your machine-learning models with data extraction and feature development Watch out for the risks of machine learning, such as underfitting or overfitting data Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms
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R 700.00
Practical Python Programming for IoT
Leverage Python and Raspberry Pi to create complex IoT applications capable of creating and detecting movement and measuring distance, light, and a host of other environmental conditionsKey FeaturesLearn the fundamentals of electronics and how to integrate them with a Raspberry PiUnderstand how to build RESTful APIs, WebSocket APIs, and MQTT-based applicationsExplore alternative approaches to structuring IoT applications with PythonBook DescriptionThe age of connected devices is here, be it fitness bands or smart homes. It's now more important than ever to understand how hardware components interact with the internet to collect and analyze user data. The Internet of Things (IoT), combined with the popular open source language Python, can be used to build powerful and intelligent IoT systems with intuitive interfaces. This book consists of three parts, with the first focusing on the "Internet" component of IoT. You'll get to grips with end-to-end IoT app development to control an LED over the internet, before learning how to build RESTful APIs, WebSocket APIs, and MQTT services in Python. The second part delves into the fundamentals behind electronics and GPIO interfacing. As you progress to the last part, you'll focus on the "Things" aspect of IoT, where you will learn how to connect and control a range of electronic sensors and actuators using Python. You'll also explore a variety of topics, such as motor control, ultrasonic sensors, and temperature measurement. Finally, you'll get up to speed with advanced IoT programming techniques in Python, integrate with IoT visualization and automation platforms, and build a comprehensive IoT project. By the end of this book, you'll be well-versed with IoT development and have the knowledge you need to build sophisticated IoT systems using Python.What you will learnUnderstand electronic interfacing with Raspberry Pi from scratchGain knowledge of building sensor and actuator electronic circuitsStructure your code in Python using Async IO, pub/sub models, and moreAutomate real-world IoT projects using sensor and actuator integrationIntegrate electronics with ThingSpeak and IFTTT to enable automationBuild and use RESTful APIs, WebSockets, and MQTT with sensors and actuatorsSet up a Raspberry Pi and Python development environment for IoT projectsWho this book is forThis IoT Python book is for application developers, IoT professionals, or anyone interested in building IoT applications using the Python programming language. It will also be particularly helpful for mid to senior-level software engineers who are experienced in desktop, web, and mobile development, but have little to no experience of electronics, physical computing, and IoT.
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R 916.00
Python 2 and 3 Compatibility
Discover clean ways to write code that will run on both Python 2 and 3.This book is tutorial-oriented with detailed examples of how to convert existing Python 2-compatible code to code that will run reliably on both Python 2 and 3. Although Python 3 is considered the future of Python, Python 2.x will be maintained for several more years, alongside Python 3, which is not backwards compatible. For those who need to support both versions, this book guides you through the process. Python 2 and 3 Compatibility explains the syntactical differences between Python 2 and 3, and how to use Python packages Python-Future and Six to implement neutral compatibility. Developers working on either small, medium, or large projects will appreciate the author's clear explanations, detailed examples, and clean techniques to help them extend support for both versions to their existing Python 2-compatible projects.What You'll LearnUnderstand the syntactical differences between Python 2 and 3Use the Six and Future librariesReview the new features in Python 3Choose which Python versions to support when doing neutral supportDecide on whether to port or provide support for both versionsWho This Book Is For Professional Python developers and enthusiasts that want to implement Python 3 support for their existing Python 2 compatible code.
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R 489.00
Programming for Computations - Python
This book is published open access under a CC BY 4.0 license. This book presents computer programming as a key method for solving mathematical problems. This second edition of the well-received book has been extensively revised: All code is now written in Python version 3.6 (no longer version 2.7). In addition, the two first chapters of the previous edition have been extended and split up into five new chapters, thus expanding the introduction to programming from 50 to 150 pages. Throughout the book, the explanations provided are now more detailed, previous examples have been modified, and new sections, examples and exercises have been added. Also, a number of small errors have been corrected. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows students to write simple programs for solving common mathematical problems with numerical methods in the context of engineering and science courses. The emphasis is on generic algorithms, clean program design, the use of functions, and automatic tests for verification.
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Learning GitHub Copilot
Supercharge your coding productivity with generative AI using GitHub Copilot. In this practical guide, author Brent Laster guides you through using generative AI for writing better code faster, generating tests with ease, creating polished documentation at any stage of development, and more. You'll also explore advanced uses-like leveraging Copilot's Agent functionality to add features autonomously and reviewing pull requests automatically.Learning GitHub Copilot is for developers, testers, DevOps engineers, and software professionals at all levels. Alongside the fundamentals, you'll dive into Copilot Edits, Agent mode, and Copilot Vision. You'll also learn how to create your own Copilot extensions to expand its capabilities. Whether you're working in Python, JavaScript, or any other language, this book helps you confidently integrate AI into your development workflow.Harness real-time AI insights to explore and understand unfamiliar code and algorithmsMaster inline completions and the chat interface to automate common tasksTurn natural language prompts into complete functions, tests, and docs quickly and easilyOptimize AI results with context and prompts to get targeted solutionsStreamline feature development and refactors with AI assistance in your IDE
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Using Asyncio in Python
If you’re among the Python developers put off by asyncio’s complexity, it’s time to take another look. Asyncio is complicated because it aims to solve problems in concurrent network programming for both framework and end-user developers. The features you need to consider are a small subset of the whole asyncio API, but picking out the right features is the tricky part. That’s where this practical book comes in.Veteran Python developer Caleb Hattingh helps you gain a basic understanding of asyncio’s building blocks—enough to get started writing simple event-based programs. You’ll learn why asyncio offers a safer alternative to preemptive multitasking (threading) and how this API provides a simple way to support thousands of simultaneous socket connections.Get a critical comparison of asyncio and threading for concurrent network programmingTake an asyncio walk-through, including a quickstart guide for hitting the ground looping with event-based programmingLearn the difference between asyncio features for end-user developers and those for framework developersUnderstand asyncio’s new async/await language syntax, including coroutines and task and future APIsGet detailed case studies (with code) of some popular asyncio-compatible third-party libraries
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Foundations of Programming, Statistics, and Machine Learning for Business Analytics
Business Analysts and Data Scientists are in huge demand, as global companies seek to digitally transform themselves and leverage their data resources to realize competitive advantage.This book covers all the fundamentals, from statistics to programming to business applications, to equip you with the solid foundational knowledge needed to progress in business analytics. Assuming no prior knowledge of programming or statistics, this book takes a simple step-by-step approach which makes potentially intimidating topics easy to understand, by keeping Maths to a minimum and including examples of business analytics in practice.Key features:· Introduces programming fundamentals using R and Python· Covers data structures, data management and manipulation and data visualization· Includes interactive coding notebooks so that you can build up your programming skills progressivelySuitable as an essential text for undergraduate and postgraduate students studying Business Analytics or as pre-reading for students studying Data Science.Ram Gopal is Pro-Dean and Professor of Information Systems at the University of Warwick.Daniel Philps is an Artificial Intelligence Researcher and Head of Rothko Investment Strategies.Tillman Weyde is Senior Lecturer at City, University of London.
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Python Programming and Numerical Methods
Python Programming and Numerical Methods: A Guide for Engineers and Scientists introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational problem-solving techniques through the use of numerical methods and the Python programming language. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level that allows students to quickly apply results in practical settings.
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R 764.00
Python Ethical Hacking from Scratch
Explore the world of practical ethical hacking by developing custom network scanning and remote access tools that will help you test the system security of your organizationKey FeaturesGet hands-on with ethical hacking and learn to think like a real-life hackerBuild practical ethical hacking tools from scratch with the help of real-world examplesLeverage Python 3 to develop malware and modify its complexitiesBook DescriptionPenetration testing enables you to evaluate the security or strength of a computer system, network, or web application that an attacker can exploit. With this book, you'll understand why Python is one of the fastest-growing programming languages for penetration testing. You'll find out how to harness the power of Python and pentesting to enhance your system security. Developers working with Python will be able to put their knowledge and experience to work with this practical guide. Complete with step-by-step explanations of essential concepts and practical examples, this book takes a hands-on approach to help you build your own pentesting tools for testing the security level of systems and networks. You'll learn how to develop your own ethical hacking tools using Python and explore hacking techniques to exploit vulnerabilities in networks and systems. Finally, you'll be able to get remote access to target systems and networks using the tools you develop and modify as per your own requirements. By the end of this ethical hacking book, you'll have developed the skills needed for building cybersecurity tools and learned how to secure your systems by thinking like a hacker.What you will learnUnderstand the core concepts of ethical hackingDevelop custom hacking tools from scratch to be used for ethical hacking purposesDiscover ways to test the cybersecurity of an organization by bypassing protection schemesDevelop attack vectors used in real cybersecurity testsTest the system security of an organization or subject by identifying and exploiting its weaknessesGain and maintain remote access to target systemsFind ways to stay undetected on target systems and local networksWho this book is forIf you want to learn ethical hacking by developing your own tools instead of just using the prebuilt tools, this book is for you. A solid understanding of fundamental Python concepts is expected. Some complex Python concepts are explained in the book, but the goal is to teach ethical hacking, not Python.
R 1,498.00
Mobile Applications Development
The book covers the concepts of Python programming language along with mobile application development. Starting from fundamentals, the book continues with the explanation of mobile app development using Kivy framework. All the chapters offer questions and exercises for to better understanding of the subject. This second revised and updated edition covers the most recent developments in Kivy since the publishing of the first edition.
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R 422.46
R 580.00
Hands-On ROS for Robotics Programming
Take your ROS skills to the next level by implementing complex robot structures in a ROS simulationKey FeaturesLearn fundamental ROS concepts and apply them to solve navigation tasksWork with single board computers to program smart behavior in mobile robotsUnderstand how specific characteristics of the physical environment influence your robot’s performanceBook DescriptionConnecting a physical robot to a robot simulation using the Robot Operating System (ROS) infrastructure is one of the most common challenges faced by ROS engineers. With this book, you'll learn how to simulate a robot in a virtual environment and achieve desired behavior in equivalent real-world scenarios.This book starts with an introduction to GoPiGo3 and the sensors and actuators with which it is equipped. You'll then work with GoPiGo3's digital twin by creating a 3D model from scratch and running a simulation in ROS using Gazebo. Next, the book will show you how to use GoPiGo3 to build and run an autonomous mobile robot that is aware of its surroundings. Finally, you'll find out how a robot can learn tasks that have not been programmed in the code but are acquired by observing its environment. You'll even cover topics such as deep learning and reinforcement learning.By the end of this robot programming book, you'll be well-versed with the basics of building specific-purpose applications in robotics and developing highly intelligent autonomous robots from scratch.What you will learnGet to grips with developing environment-aware robotsGain insights into how your robots will react in physical environmentsBreak down a desired behavior into a chain of robot actionsRelate data from sensors with context to produce adaptive responsesApply reinforcement learning to allow your robot to learn by trial and errorImplement deep learning to enable your robot to recognize its surroundingsWho this book is forIf you are an engineer looking to build AI-powered robots using the ROS framework, this book is for you. Robotics enthusiasts and hobbyists who want to develop their own ROS robotics projects will also find this book useful. Knowledge of Python and/or C++ programming and familiarity with single board computers such as Raspberry Pi is necessary to get the most out of this book.
R 2,052.00
Scientific Scripting with Python
Learn how to automate your scientific research with Python. This book teaches you the basics of the popular Python scripting language, before delving deep into all aspects of processing data. Python is a simple, yet powerful, programming language similar to Perl, Tcl, and Ruby. It is heavily used in scientific research, and by companies like Google. This book places a strong emphasis on practical techniques for handling data. Although targeted specifically at scientists and engineers, anyone who needs to automate their work flow would find it useful.
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R 2,136.00
Learn Raspberry Pi Programming with Python
Learn how to program your nifty new $35 computer to make a web spider, a weather station, a media server, and more. This book explores how to make a variety of fun and even useful projects, from a web bot to search and download files to a toy to drive your pets insane.Even if you're completely new to programming in general, you'll see how easy it is to create a home security system, an underwater photography system, an RC plane with a camera, and even a near-space weather balloon with a camera. You'll learn how to use Pi with Arduino as well as Pi with Gertboard, an expansion board with an onboard ATmega microcontroller.Learn Raspberry Pi Programming with Python has been fully updated in this new edition to cover the features of the new boards. You'll learn how to program in Python on your Raspberry Pi with hands-on examples and fun projects. What You'll LearnSet up your new Raspberry PiBuild unique projects across a range of interestsProgram basic functions and processes using PythonWho This Book Is ForReaders who want to learn Python on a fun platform like the Pi and pick up some electronics skills along the way. No programming or Linux skill required, but a little experience with Linux will be helpful. Readers familiar with the 1st edition will enjoy the updated information in this new edition.
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Multicriteria Portfolio Construction with Python
This book covers topics in portfolio management and multicriteria decision analysis (MCDA), presenting a transparent and unified methodology for the portfolio construction process. The most important feature of the book includes the proposed methodological framework that integrates two individual subsystems, the portfolio selection subsystem and the portfolio optimization subsystem. An additional highlight of the book includes the detailed, step-by-step implementation of the proposed multicriteria algorithms in Python. The implementation is presented in detail; each step is elaborately described, from the input of the data to the extraction of the results. Algorithms are organized into small cells of code, accompanied by targeted remarks and comments, in order to help the reader to fully understand their mechanics. Readers are provided with a link to access the source code through GitHub.This Work may also be considered as a reference which presents the state-of-art research on portfolio construction with multiple and complex investment objectives and constraints. The book consists of eight chapters. A brief introduction is provided in Chapter 1. The fundamental issues of modern portfolio theory are discussed in Chapter 2. In Chapter 3, the various multicriteria decision aid methods, either discrete or continuous, are concisely described. In Chapter 4, a comprehensive review of the published literature in the field of multicriteria portfolio management is considered. In Chapter 5, an integrated and original multicriteria portfolio construction methodology is developed. Chapter 6 presents the web-based information system, in which the suggested methodological framework has been implemented. In Chapter 7, the experimental application of the proposed methodology is discussed and in Chapter 8, the authors provide overall conclusions.The readership of the book aims to be a diverse group, including fund managers, risk managers, investment advisors, bankers, private investors, analytics scientists, operations researchers scientists, and computer engineers, to name just several. Portions of the book may be used as instructional for either advanced undergraduate or post-graduate courses in investment analysis, portfolio engineering, decision science, computer science, or financial engineering.
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Python Programming in A Day
Python Programming In A Day 2nd Edition: Beginners Power Guide To Learning Python Programming From Scratch What exactly is python programming and is it really that complex? How is Python made so easy so the jargon is gone and you can have success programming within a day? Want to know all about interactive mode with mathematical operations? Variables? Strings? Mr. Key is going above and beyond with data types, programming modes and conditional statements Always wanted a step by step guide to begin a program building from start to finish? Look no further! Its time for you to take advantage of this easy programming guide so you can have immediate success in Python Programming! But Now!
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