Gui Magic Mastering Real Projects In Python
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GUI Magic: Mastering Real Projects in Python
Increase your Python’s GUI programming potential with real-world projects. GUI Magic: Mastering Real Projects in Python by John Nunez is a comprehensive guide that transforms you from a Python coder into a confident GUI application developer. This book walks you through building interactive desktop applications step by step, using clear explanations and hands-on examples. Whether you're a beginner just starting out or an experienced developer looking to sharpen your GUI skills, GUI Magic offers an accessible yet in-depth journey into Python GUI development. Key Features Step-by-Step Projects: Build real-world GUI applications from scratch with clear, incremental instructions. Each project includes detailed code examples and explanations—from basic windows to complex multi-screen apps—ensuring you learn by doing and develop a portfolio of GUI projects. Major GUI Frameworks Covered: Master Python’s top GUI libraries all in one place. Create interfaces with Tkinter for quick and simple projects, PyQt5 for professional-grade applications, Kivy for touch-friendly mobile apps, and wxPython for native desktop experiences. Best Practices & Optimization: Write clean, maintainable code by following industry best practices. Learn how to optimize your GUI’s performance and responsiveness, so your applications run smoothly even as they grow in complexity. Easy Deployment: Discover how to package and distribute your Python GUI apps on multiple platforms. The book covers tools and techniques to turn your projects into standalone executables for Windows, macOS, and Linux—making it easy to share your applications with others. For Beginners & Advanced Users: Start with fundamental GUI concepts and gradually move to advanced topics like multithreading, custom widgets, and database integration. The material is approachable for first-time GUI builders, while seasoned developers will find deep insights and pro tips to elevate their skills. GUI Magic: Mastering Real Projects in Python is the perfect resource to bridge the gap between theory and practice. By the end of this book, you’ll have the confidence and skills to design professional-quality GUIs in Python. Bring your ideas to life on-screen and create applications users will love!
The Big Book of Small Python Projects
Best-selling author Al Sweigart shows you how to easily build over 80 fun programs with minimal code and maximum creativity. If you’ve mastered basic Python syntax and you’re ready to start writing programs, you’ll find The Big Book of Small Python Projects both enlightening and fun. This collection of 81 Python projects will have you making digital art, games, animations, counting pro- grams, and more right away. Once you see how the code works, you’ll practice re-creating the programs and experiment by adding your own custom touches. These simple, text-based programs are 256 lines of code or less. And whether it’s a vintage screensaver, a snail-racing game, a clickbait headline generator, or animated strands of DNA, each project is designed to be self-contained so you can easily share it online. You’ll create: • Hangman, Blackjack, and other games to play against your friends or the computer • Simulations of a forest fire, a million dice rolls, and a Japanese abacus • Animations like a virtual fish tank, a rotating cube, and a bouncing DVD logo screensaver • A first-person 3D maze game • Encryption programs that use ciphers like ROT13 and Vigenère to conceal text If you’re tired of standard step-by-step tutorials, you’ll love the learn-by-doing approach of The Big Book of Small Python Projects. It’s proof that good things come in small programs!
Mastering Azure Machine Learning
Author: Christoph Körner
language: en
Publisher: Packt Publishing Ltd
Release Date: 2020-04-30
Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using TensorFlow, Spark, and Kubernetes Key FeaturesMake sense of data on the cloud by implementing advanced analyticsTrain and optimize advanced deep learning models efficiently on Spark using Azure DatabricksDeploy machine learning models for batch and real-time scoring with Azure Kubernetes Service (AKS)Book Description The increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models. This book will help you improve your knowledge of building ML models using Azure and end-to-end ML pipelines on the cloud. The book starts with an overview of an end-to-end ML project and a guide on how to choose the right Azure service for different ML tasks. It then focuses on Azure Machine Learning and takes you through the process of data experimentation, data preparation, and feature engineering using Azure Machine Learning and Python. You'll learn advanced feature extraction techniques using natural language processing (NLP), classical ML techniques, and the secrets of both a great recommendation engine and a performant computer vision model using deep learning methods. You'll also explore how to train, optimize, and tune models using Azure Automated Machine Learning and HyperDrive, and perform distributed training on Azure. Then, you'll learn different deployment and monitoring techniques using Azure Kubernetes Services with Azure Machine Learning, along with the basics of MLOps—DevOps for ML to automate your ML process as CI/CD pipeline. By the end of this book, you'll have mastered Azure Machine Learning and be able to confidently design, build and operate scalable ML pipelines in Azure. What you will learnSetup your Azure Machine Learning workspace for data experimentation and visualizationPerform ETL, data preparation, and feature extraction using Azure best practicesImplement advanced feature extraction using NLP and word embeddingsTrain gradient boosted tree-ensembles, recommendation engines and deep neural networks on Azure Machine LearningUse hyperparameter tuning and Azure Automated Machine Learning to optimize your ML modelsEmploy distributed ML on GPU clusters using Horovod in Azure Machine LearningDeploy, operate and manage your ML models at scaleAutomated your end-to-end ML process as CI/CD pipelines for MLOpsWho this book is for This machine learning book is for data professionals, data analysts, data engineers, data scientists, or machine learning developers who want to master scalable cloud-based machine learning architectures in Azure. This book will help you use advanced Azure services to build intelligent machine learning applications. A basic understanding of Python and working knowledge of machine learning are mandatory.