Python lernen leicht gemacht, ohne ein auf den Computer heruntergeladenes Programm. Nur eine Internetverbindung reicht aus.Mit dieser Anleitung kann jeder Progr
Vertiefe deine Skills! Bearbeite diese 15 Übungsaufgaben zur print-Funktion in Python. Von Anfänger bis Fortgeschrittene.
Vertiefe deine Skills! Bearbeite diese 15 Übungsaufgaben zur print-Funktion in Python. Von Anfänger bis Fortgeschrittene.
Discover how to inject your code with highly performant Rust features to develop fast and memory-safe applications Key Features: Learn to implement Rust in a Python system without altering the entire systemWrite safe and efficient Rust code as a Python developer by understanding the essential features of RustBuild Python extensions in Rust by using Python NumPy modules in your Rust code Book Description: Python has made software development easier, but it falls short in several areas including memory management that lead to poor performance and security. Rust, on the other hand, provides memory safety without using a garbage collector, which means that with its low memory footprint, you can build high-performant and secure apps relatively easily. However, rewriting everything in Rust can be expensive and risky as there might not be package support in Rust for the problem being solved. This is where Python bindings and pip come in.This book will help you, as a Python developer, to start using Rust in your Python projects without having to manage a separate Rust server or application. Seeing as you'll already understand concepts like functions and loops, this book covers the quirks of Rust such as memory management to code Rust in a productive and structured manner. You'll explore the PyO3 crate to fuse Rust code with Python, learn how to package your fused Rust code in a pip package, and then deploy a Python Flask application in Docker that uses a private Rust pip module. Finally, you'll get to grips with advanced Rust binding topics such as inspecting Python objects and modules in Rust.By the end of this Rust book, you'll be able to develop safe and high-performant applications with better concurrency support. What You Will Learn: Explore the quirks of the Rust programming language that a Python developer needs to understand to code in RustUnderstand the trade-offs for multiprocessing and thread safety to write concurrent codeBuild and manage a software project with cargo and cratesFuse Rust code with Python so that Python can import and run Rust codeDeploy a Python Flask application in Docker that utilizes a private Rust pip moduleInspect and create your own Python objects in Rust Who this book is for: This book is for Python developers who want to speed up their Python code with Rust and implement Rust in a Python system without altering the entire system. You'll be able to learn about all topics relating to Rust programming. Basic knowledge of Python is required to get the most out of this book.
Diese Basics in Python musst du wissen. Wenn du all diese Funktionen in Python kennst, bist du auf einem guten Weg als Fortgeschrittener!
Highlights The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. About the Author: Susan E. McGregor is a researcher at Columbia University's Data Science Institute, where she also cochairs its Center for Data, Media and Society. 413 Pages Computers + Internet, Databases Description Book Synopsis The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations. Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources Understand and use programming basics in Python to wrangle data at scale Organize, document, and structure your code using best practices Collect data from structured data files, web pages, and APIs Perform basic statistical analyses to make meaning from datasets Visualize and present data in clear and compelling ways About the Author Susan E. McGregor is a researcher at Columbia University's Data Science Institute, where she also cochairs its Center for Data, Media and Society. For over a decade, she has been refining her approach to teaching programming and data analysis to non-STEM learners at the professional, graduate, and undergraduate levels. McGregor has been a full-time faculty member and researcher at Columbia University since 2011, when she joined Columbia Journalism School and the Tow Center for Digital Journalism. While there, she developed the school's first data journalism curriculum and served as a primary academic advisor for its dual-degree program in Journalism and Computer Science. Her academic research centers on security and privacy issues affecting journalists and media organizations, and is the subject of her first book, Information Security Essentials: A Guide for Reporters, Editors, and Newsroom Leaders (CUP). Prior to her work at Columbia, McGregor spent several years as the Senior Programmer on the News Graphics team at the Wall Street Journal. She was named a 2010 Gerald Loeb Award winner for her work on WSJ's original What They Know series, and has spoken and published at a range of leading academic security and privacy conferences. Her work has received support from the National Science Foundation, the Knight Foundation, Google, and multiple schools and offices of Columbia University. McGregor is also interested in how the arts can help stimulate critical thinking and introduce new perspectives around technology issues. She holds a master's degree in Educational Communication and Technology from NYU and a bachelor's degree in Interactive Information Design from Harvard University.
Morning meetings are a great way to start the day, but they can be challenging to keep fresh and engaging. That's where our 32 interactive digital games come in! These games are perfect for early elementary students and are designed to build classroom community, promote critical thinking, and improv...
Scratch und Python mit der neuen LEGO-Roboter-Generation Programmieren lernen leicht gemacht: Steuerungsbefehle schreiben und real mit LEGO-Robotern ausführen Beispiele in Scratch und Python Für die neue LEGO-Mindstorms-Generation »Robot Inventor« und den kompatible Spike Prime Programmieren lernen muss nicht theoretisch sein: Zusammen mit den LEGO-Modellreihen Mindstorms Robot Inventor 51515 oder dem kompatiblen Spike Prime können Sie Ihre Programmzeilen direkt mit selbstgebauten Modellen ausprobieren. Die Beispiele in diesem Buch erklären Schritt für Schritt, was gutes und effizientes Programmieren ausmacht. Die direkte Ausführung mit einem Roboter macht mehr Spaß als Befehlebüffeln und führt auf praktische Weise zum Lernerfolg. Das Buch bietet einen methodisch sinnvollen Weg, die zwei Sprachen zu erlernen, die LEGO für die Modellreihen vorsieht. Leserinnen und Leser können die Lösungen zu Programmier-Aufgabenstellungen jeweils in beiden Sprachen verfolgen und lernen dabei ihre Unterschiede und Stärken kennen: Scratch, das mit grafischen Textblöcken arbeitet, eignet sich besonders gut für Einsteigerinnen und Einsteiger. Python dient als einfacher Zugang zur textbasierten Programmierung und ermöglicht auch komplizierte Abläufe. Experimente und intuitives Lernen mit dem exklusiven Beispielroboter, der aus Teilen der Sets gebaut werden kann. Das Robotermodell lässt sich aus Teilen des Sets LEGO Mindstorms Robot Inventor 51515 bzw. dem LEGO-Education-Spike-Prime-Set 45678 aufbauen. Mehr anzeigen
Highlights Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. Author(s): Michael Munn & David Pitman 276 Pages Computers + Internet, Description Book Synopsis Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does. Explainability methods provide an essential toolkit for better understanding model behavior, and this practical guide brings together best-in-class techniques for model explainability. Experienced machine learning engineers and data scientists will learn hands-on how these techniques work so that you'll be able to apply these tools more easily in your daily workflow. This essential book provides: A detailed look at some of the most useful and commonly used explainability techniques, highlighting pros and cons to help you choose the best tool for your needs Tips and best practices for implementing these techniques A guide to interacting with explainability and how to avoid common pitfalls The knowledge you need to incorporate explainability in your ML workflow to help build more robust ML systems Advice about explainable AI techniques, including how to apply techniques to models that consume tabular, image, or text data Example implementation code in Python using well-known explainability libraries for models built in Keras and TensorFlow 2.0, PyTorch, and HuggingFace
Highlights Mine the rich data tucked away in popular social websites such as Twitter, Facebook, LinkedIn, and Instagram. About the Author: Matthew Russell (@ptwobrussell) is Chief Technology Officer at Built Technologies, where he leads a team of leaders on a mission to improve the way the world is built. 426 Pages Computers + Internet, Web Description About the Book "Mine the rich data tucked away in popular social websites like Twitter, Facebook, LinkedIn, Instagram, and GitHub. With the third edition of this popular guide, data scientists, analysts,and programmers will learn how to glean insights from social media--who's connecting with whom, what they're talking about, and where they're located--using Python code examples, Jupyter notebooks, or Docker containers."--Back cove Book Synopsis Mine the rich data tucked away in popular social websites such as Twitter, Facebook, LinkedIn, and Instagram. With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media--including who's connecting with whom, what they're talking about, and where they're located--using Python code examples, Jupyter notebooks, or Docker containers. In part one, each standalone chapter focuses on one aspect of the social landscape, including each of the major social sites, as well as web pages, blogs and feeds, mailboxes, GitHub, and a newly added chapter covering Instagram. Part two provides a cookbook with two dozen bite-size recipes for solving particular issues with Twitter. Get a straightforward synopsis of the social web landscape Use Docker to easily run each chapter's example code, packaged as a Jupyter notebook Adapt and contribute to the code's open source GitHub repository Learn how to employ best-in-class Python 3 tools to slice and dice the data you collect Apply advanced mining techniques such as TFIDF, cosine similarity, collocation analysis, clique detection, and image recognition Build beautiful data visualizations with Python and JavaScript toolkits About the Author Matthew Russell (@ptwobrussell) is Chief Technology Officer at Built Technologies, where he leads a team of leaders on a mission to improve the way the world is built. Outside of work, he contemplates ultimate reality, practices rugged individualism, and trains for the possibilities of a zombie or robot apocalypse. Mikhail Klassen is Chief Data Scientist at Paladin AI, a startup creating adaptive training technologies. He has a PhD in computational astrophysics from McMaster University and a BS in applied physics from Columbia University. Mikhail is passionate about artificial intelligence and how the tools of data science can be used for good. When not working at a startup, he's usually reading or traveling.
ELECFREAKS Smart Coding Watch Kit is a wearable device based on micro:bit button cell extension board Pro, a DIY micro:bit watch can be easily made with a simple installing method. ELECFREAKS is an official Partner of micro:bit Educational Foundation focusing on developing educational and creative micro:bit accessories for the world. We devote ourselves to providing the most complete and excellent products and services to our customers. We have created tutorial blogs, learning materials, videos, and fun case studies as part of building global micro:bit communities in education. Support Mutiple Programming The fun cases will bring children the joy of programming! Children can use programming to achieve what they want. It better improves children's interest in programming! Teachers or parents also can give the child some help through communication to let the child have fun in programming! Parameter Name: Wear:bit Working Voltage: 2.7~3.3V Buzzer: Support Size: 49.1x51.6mm Net Weight:12.7g Only Support 2025 Button Cells. Important: WITHOUT micro: bit and BATTERY. Characteristic For Wear:bit Powered by two 3V CR2025 lithium batteries. Loaded with a buzzer that is controlled through the P0 port. Loaded with a buzzer switch. It can be used with the watch strap and the micro:bit. The Breakthroughs Simplify the installation without using the acrylic back shroud. Maintain a simple style with 3-pin ports canceled. Upgrade the function by adding a switch for the buzzer. Packing List
In this article, we are going to learn all about the Python DateTime module with the help of examples. Python DateTime module plays the most important role
Programmier-Apps helfen dir, die Grundzüge des Codens zu erlernen. Sie vermitteln dir erstes Wissen in Programmiersprachen wie JavaScript, Swift & viele mehr. Welche Apps empfehlenswert sind, erfährst du in diesem Ratgeber.
Learn Python.
Python lists are arrayable elements which contain heterogeneous data values. It can have any numbers of rows. These lists can be sorted or modified.
In this article, you will learn all about How to read CSV files in Python with the help of examples. Here we are going to use a built-in CSV module.
A comprehensive introduction and guide for those interested in learning the programming language known as Python, and how to create and experiment with various projects made easily possible by the said language Have you been thinking of learning programming? How about learning the Python language? Are you looking for that informative and beginner-friendly material to help you create projects on your own? If it's a yes to these questions, then you just came across the right book to help you!Having included an array of insightful modules and procedures found within this guide, Python Projects For Beginners serves as the ultimate guide that will introduce its readers to data science, coding, programming, and analysis. Intended to be an educational material that will assist anyone unfamiliar in creating Python projects, this book is sure to groom anyone into quickly becoming a reasonably knowledgeable and skilled individual in the programming field of the Python language.Readers can expect to be informed about: - The differences between Python 2 and 3;- The Python variables and operators;- The several data types and data structures;- Generating strings, loops, and conditional statements;- Numerous projects and web applications that you can try; All of these are potential takeaways that you can acquire just by reading this book, so much so that we guarantee that by the end of this book, you will have been well-versed enough actually to create something on your own.Get this book to get started training those fingers to know how to code with Python now!
Bist du Schüler oder Student und möchtest deine Motivation zum Lernen steigern? Mit diesen 47 Tipps für mehr Lernmotivation gelingt es dir.
Mit einem Lernvideo kann man schnell und einfach von überall aus neues Wissen erlagen und so bessere Noten in der Schule bekommen
Bei fast allen Schülern ist sie bekannt und gefürchtet: die mündliche Prüfung. Dies sind die häufigsten Gründe für eine solche Prüfung: Du hast das 4. Abiturfach als mündliches Prüfungsfach. Du hast deutliche Abweichung von der Vornote in einem schriftlichen Prüfungsfach. Du musst eine Nachprüfung machen. Du musst einen Ersatz für eine Klassenarbeit in der Fremdsprache ... Weiterlesen
Einen guten Lernplan zu erstellen, ist keine Zeitverschwendung - im Gegenteil (weil du bereits beim Erstellen des Plans lernst).
Wenn du deinen Lerntypen kennst, kannst du viel schneller und einfacher lernen. Mach einen Lerntypentest und optimiere deinen Lernerfolg! KLICK HIER
Lernen lernen aber effektiv: Hol dir wertvolle Tipps, um als Student erfolgreich zu sein. Erfahre, wie du effektiv lernen lernen kannst!
Musst du viel auswendig lernen und das in möglichst kurzer Zeit? Hier finest du die besten Tipps zum auswendig lernen für Schule und Studium.
Aus eigener Erfahrung gibt es 5 Dinge, die du 24 Stunden vor einer Prüfung tun solltest und 5 Dinge, die du lieber lässt. - Prüfungsvorbereitung Tipps
Die Welt des Lernens kann manchmal verwirrend sein, besonders wenn es um die Bedürfnisse deines Kindes geht. Aber keine Sorge, wir bringen Licht ins Dunkel. Wenn du nämlich den Lerntypen deines Kindes kennst, hast du einen entscheidenden Schlüssel, um das Lernen zu einer spannenden Reise zu machen. Finde heraus, welcher Lerntyp am besten zu deinem ... Weiterlesen
Lernmethoden sind unerlässlich, um erfolgreich zu lernen. Daher habe ich dir eine Übersicht mit Tipps, Anleitungen & Beispielen zusammen gestellt.
Musst du viel auswendig lernen und das in möglichst kurzer Zeit? Hier finest du die besten Tipps zum auswendig lernen für Schule und Studium.
Hier erklären wir dir, wie du ein Lernplakat erstellen kannst - mit dieser Methode kannst du dein Wissen zu einem Thema visualisieren
8 wichtige Tipps für eine erfolgreiche Nachprüfung! Die gute Nachricht zuerst: Die ersten zwei bis drei Wochen sollt ihr unbedingt für die Erholung nützen.
Lernen lernen aber effektiv: Hol dir wertvolle Tipps, um als Student erfolgreich zu sein. Erfahre, wie du effektiv lernen lernen kannst!
Lernen kann so einfach sein und sogar Spaß machen! Man muss nur ein paar simple Tipps beachten, dann läuft es fast von selbst. Die besten Lerntipps für Schüler, Studenten und alle anderen Lernwilligen
