Die praktische Informatik lebt vom Ausprobieren verschiedener Lösungswege; dem Experimentieren mit Programmkonstrukten und Algorithmen, und allgemein vom Selbermachen. Darauf baut das didaktische Konzept des Buchs auf: Anhand einer Vielzahl an Aufgaben kann der Student die präsentierten Konzepte selbst erfahren, mit Ihnen arbeiten und so die eigentlichen Probleme der Informatik wirklich verstehen.
The practice of computer science thrives on trying out different solution pathways, experimenting with program constructs and algorithms, and, in general, from hands-on exploration. A do it yourself approach lies at the heart of this textbook’s teaching method: by solving numerous exercises, the student personally experiences and works with the concepts to be imparted, and comes to truly understand computer science problems.
Insbesondere die praktische Informatik lebt vom Ausprobieren und Selbermachen. Darauf baut das didaktische Konzept dieses Buches auf: Alle wichtigen klassischen Algorithmen werden so erklärt, dass sie direkt mit Python geübt werden können. Durch diese unmittelbare praktische Anwendung der theoretischen Inhalte gestaltet sich der Lernprozess deutlich interessanter und effektiver.
Based on the latest version of the language, this book offers a self-contained, concise and coherent introduction to programming with Python. The books primary focus is on realistic case study applications of Python. Each practical example is accompanied by a brief explanation of the problem-terminology and concepts, followed by necessary program development in Python using its constructs, and simulated testing. Given the open and participatory nature of development, Python has a variety of incorporated data structures, which has made it difficult to present it in a coherent manner. Further, some advanced concepts (super, yield, generator, decorator, etc.) are not easy to explain. The book specially addresses these challenges; starting with a minimal subset of the core, it offers users a step-by-step guide to achieving proficiency. Dr. T. R. Padmanabhan was formerly Professor Emeritus at Amrita Vishwa Vidyapeetham, Coimbatore. He taught at the IIT Kharagpur, before doing R & D for private companies for several years. He is a Senior Member of the IEEE and a Fellow of both the Institution of Engineers (IEI) and the Institution of Electronics and Telecommunication Engineers (IETE). He has previously published books with Wiley, Tata McGraw-Hill, and Springer Verlag.
Get started in the world of software development: go from zero knowledge of programming to comfortably writing small to medium-sized programs in Python. Programming can be intimidating (especially when most books on software require you to know and use obscure command line instructions) but it doesnt have to be that way! In Learn to Program with Python , author Irv Kalb uses his in-person teaching experience to guide you through learning the Python computer programming language. He uses a conversational style to make you feel as though he is your personal tutor. All material is laid out in a thoughtful manner, each lesson building on previous ones. Many real-world analogies make the material easy to relate to. A wide variety of well-documented examples are provided. Along the way, youll develop small programs on your own through a series of coding challenges that reinforce the content of the chapters. What You Will Learn: Learn fundamental programming concepts including: variables and assignment statements, functions, conditionals, loops, lists, strings, file input and output, Internet data, and data structures Get comfortable with the free IDLE Interactive Development Environment (IDE), which you will use to write and debug all your Python code - no need to use the command line! Build text-based programs, including a number of simple games Learn how to re-use code by building your own modules Use Pythons built-in data structures and packages to represent and make use of complex data from the Internet Who this book is for: This book assumes that you have absolutely no prior knowledge about programming. There is no need to learn or use any obscure Unix commands. Students of any age who have had no exposure to programming and are interested in learning to do software development in the Python language. The book can be used as a text book associated with a high school or college introduction to computer science course. Secondly, people who have had exposure to some computer language other than Python, who would like to build good habits for programming in Python. Irv Kalb has a BS and MS in Computer Science. He has worked as a software developer, manager of software developers, manager of software development projects, and as a teacher of software for entire career. He has worked both as an employee for a number of technical companies and for many years as an independent consultant. He has been developing been writing technical articles and ebooks about software since 2000, and has been teaching software development in Silicon Valley colleges since 2010.
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions.
Write your own Digital Image Processing programs with the use of pillow, scipy.ndimage, and matplotlib in Python 3 with Raspberry Pi 3 as the hardware platform. This concise quick-start guide provides working code examples and exercises. Learn how to interface Raspberry Pi with various image sensors. What Youll Learn •Understand Raspberry Pi concepts and setup •Understand digital image processing concepts •Study pillow, the friendly PIL fork •Explore scipy.ndimage and matplotlib •Master use of the Pi camera and webcam Who This Book Is For Raspberry Pi and IoT enthusiasts, digital image processing enthusiasts, Python and Open Source enthusiasts and professionals Ashwin Pajankar is a Programmer, a Maker, an Author, a Youtuber, and an Educator with more than 10 years experience in software design, development, testing, and automation. He graduated from the coveted IIIT Hyderabad, earning an M.Tech in computer science and engineering. He holds multiple professional certifications from Oracle, IBM, Teradata, and ISTQB in development, databases, and testing. He has won several awards in college through outreach initiatives, at work for technical achievements, and community service through corporate social responsibility programs.
Das umfassende Handbuch. Grundlagen verstehen, spannende Projekte realisieren. Schnittstellen des Pi, Schaltungsaufbau, Steuerung mit Python. Erweiterungen fuer den Pi: Gertboard, PiFace, Quick2Wire u. a.Gebundenes BuchAktuell zu Raspberry Pi 3 und Zero so
Dieses Buch befasst sich mit der Hardwareauswahl und Softwareentwicklung eines kostengünstigen und einfach zu bedienenden Roboters, welcher über einen Raspberry Pi 2 gesteuert wird. Der Raspberry Pi läuft mit einem Linux Betriebssystem und alle Codebeispiele sind in Python geschrieben. Alle Kosten der benötigten Komponenten sollten möglichst gering und die Beschaffung problemlos sein. Ebenso sollte der Roboter einfach zu bedienen und anhand von Source-Code Beispielen zum Nachbauen geeignet sein. Am Ende des Buches verfügt der Roboter über die folgenden wesentlichen Funktionen: autonomes Fahren mit einem Fahrgestellt auf 4 Rädern, Ultraschalldistanzsensor zum Erkennen von Hindernissen, Servomotoren zum Bewegen der Kamera, Kamera für die farbliche Objekterkennung, Mikrofon + Lautsprecher, z.B. für Sprachkommandos, berührungsempfindliche Anzeige zum Steuern des Roboters.
Wring more out of the data with a scientific approach toanalysis Graph Analysis and Visualization brings graph theory outof the lab and into the real world. Using sophisticated methods andtools that span analysis functions, this guide shows you how toexploit graph and network analytic techniques to enable thediscovery of new business insights and opportunities. Published infull color, the book describes the process of creating powerfulvisualizations using a rich and engaging set of examples fromsports, finance, marketing, security, social media, and more. Youwill find practical guidance toward pattern identification andusing various data sources, including Big Data, plus clearinstruction on the use of software and programming. The companionwebsite offers data sets, full code examples in Python, and linksto all the tools covered in the book. Science has already reaped the benefit of network and graphtheory, which has powered breakthroughs in physics, economics,genetics, and more. This book brings those proven techniques intothe world of business, finance, strategy, and design, helpingextract more information from data and better communicate theresults to decision-makers. Study graphical examples of networks using clear and insightfulvisualizations Analyze specifically-curated, easy-to-use data sets fromvarious industries Learn the software tools and programming languages that extractinsights from data Code examples using the popular Python programminglanguage There is a tremendous body of scientific work on network andgraph theory, but very little of it directly applies to analystfunctions outside of the core sciences – until now. Writtenfor those seeking empirically based, systematic analysis methodsand powerful tools that apply outside the lab, Graph Analysisand Visualization is a thorough, authoritative resource.