Python
Aymen El Amri
“OpenAI GPT for Python Developers” is meticulously crafted to provide Python developers with a deep dive into the mechanics and applications of GPT technology, beginning with a captivating narrative on the evolution of OpenAI and the fundamental workings of GPT models. As readers progress, they will be expertly guided through the essential steps of setting up a development environment tailored for AI innovations, coupled with insightful advice on selecting the most appropriate GPT model to suit specific project needs.The guide progresses into practical tutorials that cover the implementation of chat completions and the art of prompt engineering, providing a solid foundation in harnessing the capabilities of GPT for generating human-like text responses. Practical applications are further expanded with discussions on the creation of autonomous AI-to-AI dialogues, the development of AI avatars, and the strategic use of AI in interactive applications.In addition to technical skills, this book addresses the ethical implications and prospects of AI technologies, encouraging a holistic view of AI development. The guide is enriched with detailed examples, step-by-step tutorials, and comprehensive explanations that illuminate the theoretical aspects and emphasize practical implementation.
Aleksei Spizhevoi, Aleksandr Rybnikov
OpenCV 3 is a native cross-platform library for computer vision, machine learning, and image processing. OpenCV's convenient high-level APIs hide very powerful internals designed for computational efficiency that can take advantage of multicore and GPU processing. This book will help you tackle increasingly challenging computer vision problems by providing a number of recipes that you can use to improve your applications.In this book, you will learn how to process an image by manipulating pixels and analyze an image using histograms. Then, we'll show you how to apply image filters to enhance image content and exploit the image geometry in order to relay different views of a pictured scene. We’ll explore techniques to achieve camera calibration and perform a multiple-view analysis.Later, you’ll work on reconstructing a 3D scene from images, converting low-level pixel information to high-level concepts for applications such as object detection and recognition. You’ll also discover how to process video from files or cameras and how to detect and track moving objects. Finally, you'll get acquainted with recent approaches in deep learning and neural networks.By the end of the book, you’ll be able to apply your skills in OpenCV to create computer vision applications in various domains.
Gabriel Garrido Calvo, Prateek Joshi
Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease.We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples.This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications.
Dr. Menua Gevorgyan, Arsen Mamikonyan, Michael Beyeler
OpenCV is a native cross-platform C++ library for computer vision, machine learning, and image processing. It is increasingly being adopted in Python for development. This book will get you hands-on with a wide range of intermediate to advanced projects using the latest version of the framework and language, OpenCV 4 and Python 3.8, instead of only covering the core concepts of OpenCV in theoretical lessons. This updated second edition will guide you through working on independent hands-on projects that focus on essential OpenCV concepts such as image processing, object detection, image manipulation, object tracking, and 3D scene reconstruction, in addition to statistical learning and neural networks.You’ll begin with concepts such as image filters, Kinect depth sensor, and feature matching. As you advance, you’ll not only get hands-on with reconstructing and visualizing a scene in 3D but also learn to track visually salient objects. The book will help you further build on your skills by demonstrating how to recognize traffic signs and emotions on faces. Later, you’ll understand how to align images, and detect and track objects using neural networks.By the end of this OpenCV Python book, you’ll have gained hands-on experience and become proficient at developing advanced computer vision apps according to specific business needs.
William Ayd, Matthew Harrison, Wes McKinney
Unlock the full power of pandas 2.x with this hands-on cookbook, designed for Python developers, data analysts, and data scientists who need fast, efficient solutions for real-world data challenges. This book provides practical, ready-to-use recipes to streamline your workflow. With step-by-step guidance, you'll master data wrangling, visualization, performance optimization, and scalable data analysis using pandas’ most powerful features. From importing and merging large datasets to advanced time series analysis and SQL-like operations, this cookbook equips you with the tools to analyze, manipulate, and visualize data like a pro. Learn how to boost efficiency, optimize memory usage, and seamlessly integrate pandas with NumPy, PyArrow, and databases. This book will help you transform raw data into actionable insights with ease.*Email sign-up and proof of purchase required
Theodore Petrou
This book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas 0.20. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way.The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands like one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter.Many advanced recipes combine several different features across the pandas 0.20 library to generate results.
William Ayd, Matthew Harrison
Pandas to najpopularniejsza biblioteka Pythona do przetwarzania danych. Jednak nawet doświadczeni użytkownicy tego darmowego narzędzia często nie znają jego wszystkich imponujących, a przy tym wyjątkowo przydatnych funkcji. Choć oficjalna dokumentacja pandas jest obszerna, brakuje w niej praktycznych przykładów pokazujących, jak łączyć wiele poleceń a to właśnie okazuje się kluczowe! Książka powstała z myślą o wszystkich, którzy zajmują się analizą danych bez względu na poziom doświadczenia. Została pomyślana tak, aby w klarowny i praktyczny sposób, krok po kroku wyjaśnić wykonywanie różnych operacji na danych: od podstawowych czynności przetwarzania danych po zaawansowane techniki obsługi dużych zbiorów. Poszczególne receptury przygotowano w czytelnej konwencji: Jak to zrobić? Jak to działa? To jeszcze nie wszystko Każda receptura jest niezależna od innych, a układ treści pozwala na łatwe i szybkie odnalezienie potrzebnego zagadnienia. W książce między innymi: system typów pandas eksploracja danych za pomocą biblioteki pandas grupowanie, agregowanie, przekształcanie i łączenie danych z różnych źródeł niezawodne szeregi czasowe i skalowanie operacji w pandas ekosystem biblioteki pandas Doskonałe źródło praktycznych rozwiązań typowych problemów, z którymi spotkasz się w swojej pracy analitycznej w Pythonie! Wes McKinney, twórca projektów pandas i Ibis