Python is a very powerful, high-level, object-oriented programming language. It has swiftly developed over the years to become the language of choice for software developers due to its simplicity. This book takes you through varied and real-life projects. The examples start with the basics and gradually increase in complexity, helping boost ...

Intended for seasoned Go programmers who want to put their expertise in Go to use to solve big, real-world, modern problems. With a basic understanding of channels and goroutines, you will hone your skills to build tools and programs that are quick and simple. You need not be an expert in distributed systems or technologies in order to deliver solutions capable of great scale. It is assumed that you are familiar with the basic concepts of Go.

Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving complex challenges. But it's not always clear which NLP tools or libraries would work for a business's needs, or which techniques you should use and in what order. This practical book provides data scientists and developers with blueprints for best practice solutions to common tasks in text analytics and natural language processing. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler provide real-world case studies and detailed code examples in Python to help you get started quickly. Extract data from APIs and web pages Prepare textual data for statistical analysis and machine learning Use machine learning for classification, topic modeling, and summarization Explain AI models and classification results Explore and visualize semantic similarities with word embeddings Identify customer sentiment in product reviews Create a knowledge graph based on named entities and their relations

Get to grips with traditional computer vision algorithms and deep learning approaches, and build real-world applications with OpenCV and other machine learning frameworks Key FeaturesUnderstand how to capture high-quality image data, detect and track objects, and process the actions of animals or humansImplement your learning in different areas of computer visionExplore advanced concepts in OpenCV such as machine learning, artificial neural network, and augmented realityBook Description 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. What you will learnGenerate real-time visual effects using filters and image manipulation techniques such as dodging and burningRecognize hand gestures in real-time and perform hand-shape analysis based on the output of a Microsoft Kinect sensorLearn feature extraction and feature matching to track arbitrary objects of interestReconstruct a 3D real-world scene using 2D camera motion and camera reprojection techniquesDetect faces using a cascade classifier and identify emotions in human faces using multilayer perceptronsClassify, localize, and detect objects with deep neural networksWho this book is for This book is for intermediate-level OpenCV users who are looking to enhance their skills by developing advanced applications. Familiarity with OpenCV concepts and Python libraries, and basic knowledge of the Python programming language are assumed.

Design and develop advanced computer vision projects using OpenCV with PythonAbout This Book* Program advanced computer vision applications in Python using different features of the OpenCV library* Practical end-to-end project covering an important computer vision problem* All projects in the book include a step-by-step guide to create computer vision applicationsWho This Book Is ForThis book is for intermediate users of OpenCV who aim to master their skills by developing advanced practical applications. Readers are expected to be familiar with OpenCV's concepts and Python libraries. Basic knowledge of Python programming is expected and assumed.What You Will Learn* Generate real-time visual effects using different filters and image manipulation techniques such as dodging and burning* Recognize hand gestures in real time and perform hand-shape analysis based on the output of a Microsoft Kinect sensor* Learn feature extraction and feature matching for tracking arbitrary objects of interest* Reconstruct a 3D real-world scene from 2D camera motion and common camera reprojection techniques* Track visually salient objects by searching for and focusing on important regions of an image* Detect faces using a cascade classifier and recognize emotional expressions in human faces using multi-layer peceptrons (MLPs)* Recognize street signs using a multi-class adaptation of support vector machines (SVMs)* Strengthen your OpenCV2 skills and learn how to use new OpenCV3 featuresIn DetailOpenCV is a native cross platform C++ Library for computer vision, machine learning, and image processing. It is increasingly being adopted in Python for development. OpenCV has C++/C, Python, and Java interfaces with support for Windows, Linux, Mac, iOS, and Android. Developers using OpenCV build applications to process visual data; this can include live streaming data from a device like a camera, such as photographs or videos. OpenCV offers extensive libraries with over 500 functionsThis book demonstrates how to develop a series of intermediate to advanced projects using OpenCV and Python, rather than teaching the core concepts of OpenCV in theoretical lessons. Instead, the working projects developed in this book teach the reader how to apply their theoretical knowledge to topics such as image manipulation, augmented reality, object tracking, 3D scene reconstruction, statistical learning, and object categorization.By the end of this book, readers will be OpenCV experts whose newly gained experience allows them to develop their own advanced computer vision applications.Style and approachThis book covers independent hands-on projects that teach important computer vision concepts like image processing and machine learning for OpenCV with multiple examples.

Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You’ll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You’ll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples. This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategies Dimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve construction Algorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio management Reinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio management NLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations

Master GUI programming in Tkinter as you design, implement, and deliver ten real-world applications from start to finish About This Book Conceptualize and build state-of-art GUI applications with Tkinter Tackle the complexity of just about any size GUI application with a structured and scalable approach A project-based, practical guide to get hands-on into Tkinter GUI development Who This Book Is For Software developers, scientists, researchers, engineers, students, or programming hobbyists with basic familiarity in Python will find this book interesting and informative. People familiar with basic programming constructs in other programming language can also catch up with some brief reading on Python. No GUI programming experience is expected. What You Will Learn Get to know the basic concepts of GUI programming, such as Tkinter top-level widgets, geometry management, event handling, using callbacks, custom styling, and dialogs Create apps that can be scaled in size or complexity without breaking down the core Write your own GUI framework for maximum code reuse Build apps using both procedural and OOP styles, understanding the strengths and limitations of both styles Learn to structure and build large GUI applications based on Model-View-Controller (MVC) architecture Build multithreaded and database-driven apps Create apps that leverage resources from the network Learn basics of 2D and 3D animation in GUI applications Develop apps that can persist application data with object serialization and tools such as configparser In Detail Tkinter is the built-in GUI package that comes with standard Python distributions. It is a cross-platform package, which means you build once and deploy everywhere. It is simple to use and intuitive in nature, making it suitable for programmers and non-programmers alike. This book will help you master the art of GUI programming. It delivers the bigger picture of GUI programming by building real-world, productive, and fun applications such as a text editor, drum machine, game of chess, media player, drawing application, chat application, screen saver, port scanner, and many more. In every project, you will build on the skills acquired in the previous project and gain more expertise. You will learn to write multithreaded programs, network programs, database driven programs and more. You will also get to know the modern best practices involved in writing GUI apps. With its rich source of sample code, you can build upon the knowledge gained with this book and use it in your own projects in the discipline of your choice. Style and approach An easy-to-follow guide, full of hands-on examples of real-world GUI programs. The first chapter is a must read as it explains most of the things you need to get started with writing GUI programs with Tkinter. Each subsequent chapter is a stand-alone project that discusses some aspects of GUI programming in detail. These chapters can be read sequentially or randomly depending upon the readers experience with Python.