Библиотека Python разработчика | Книги по питону

Python for Finance Yuxing Yan (2017) Understand the fundamentals of Python data structures and work with time-series data Implement key concepts in quantitative finance using popular Python libraries such as NumPy, SciPy, and matplotlib A step-by-step tutorial packed with many Python programs that will help you learn how to apply Python to finance This book assumes that the readers have some basic knowledge related to Python. However, he/she has no knowledge of quantitative finance. In addition, he/she has no knowledge about financial data.

Opencv 3 Computer Vision Application Programming Cookbook, Third Edition Robert Laganiere (2017) OpenCV 3 Computer Vision Application Programming Cookbook Third Edition provides a complete introduction to the OpenCV library and explains how to build your first computer vision program. You will be presented with a variety of computer vision algorithms and exposed to important concepts in image and video analysis that will enable you to build your own computer vision applications. This book helps you to get started with the library, and shows you how to install and deploy the OpenCV library to write effective computer vision applications following good programming practices. You will learn how to read and write images and manipulate their pixels. Different techniques for image enhancement and shape analysis will be presented. You will learn how to detect specific image features such as lines, circles or corners. You will be introduced to the concepts of mathematical morphology and image filtering.

Python network programming : conquer all your networking challenges with the powerful Python language Chou, Eric, Kathiravelu, Pradeeban, Ratan, Abhishek, Sarker, M. O. Faruque (2019) Key Features Master Python skills to develop powerful network applications Grasp the fundamentals and functionalities of SDN Design multi-threaded, event-driven architectures for echo and chat servers

A Smarter Way to Learn Python: Learn it faster. Remember it longer Mark Myers (2017) I was smart enough to earn an honors degree in philosophy from Harvard, but an aptitude test told me to avoid computer programming. I'm sure it was right. But then I designed a learning system for myself that quadrupled my aptitude for learning computer languages. It worked so well for me that I've used it to teach coding to grandmothers, cab drivers, musicians, and 50,000 other newbies.

Scikit-Learn Cookbook: Over 80 Recipes for Machine Learning in Python With Scikit-Learn Julian Avila (2017) Handle a variety of machine learning tasks effortlessly by leveraging the power of scikit-learn Perform supervised and unsupervised learning with ease, and evaluate the performance of your model Practical, easy to understand recipes aimed at helping you choose the right machine learning algorithm

Impractical Python Projects: Playful Programming Activities to Make You Smarter Lee Vaughan (2018) Impractical Python Projectsis a collection of fun and educational projects designed to entertain programmers while enhancing their Python skills. It picks up where the complete beginner books leave off, expanding on existing concepts and introducing new tools that you'll use every day. And to keep things interesting, each project includes a zany twist featuring historical incidents, pop culture references, and literary allusions.

Hands-On Penetration Testing with Python Enhance your ethical hacking skills to build automated and intelligent systems Furqan Khan (2019) With the current technological and infrastructural shift, penetration testing is no longer a process-oriented activity. Modern-day penetration testing demands intensive automation and innovation, and Python is at the forefront. Given the huge number of tools written in Python and its popularity in the penetration testing space, this language has always been the first choice for penetration testers.

Applied Data Science with Python and Jupyter Alex Galea (2018) Getting started with data science doesn't have to be an uphill battle. Applied Data Science with Python and Jupyter is a step-by-step guide ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction to these concepts. In this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. After familiarizing ourselves with its standard features, you'll look at an example of it in practice with our first analysis. In the next lesson, you dive right into predictive analytics, where multiple classification algorithms are implemented. Finally, the book ends by looking at data collection techniques. You'll see how web data can be acquired with scraping techniques and via APIs, and then briefly explore interactive visualizations.

Qt5 Python GUI Programming Cookbook: Building responsive and powerful cross-platform applications with PyQt B.M. Harwani (2018) PyQt is one of the best cross-platform interface toolkits currently available; it's stable, mature, and completely native. If you want control over all aspects of UI elements, PyQt is what you need. This book will guide you through every concept necessary to create fully functional GUI applications using PyQt, with only a few lines of code. As you expand your GUI using more widgets, you will cover networks, databases, and graphical libraries that greatly enhance its functionality. Next, the book guides you in using Qt Designer to design user interfaces and implementing and testing dialogs, events, the clipboard, and drag and drop functionality to customize your GUI. You will learn a variety of topics, such as look and feel customization, GUI animation, graphics rendering, implementing Google Maps, and more.

Программируем на Python Майкл Доусон (2014) Эта книга - идеальное пособие для начинающих изучать Python. Руководство, написанное опытным разработчиком и преподавателем, научит фундаментальным принципам программирования на примере создания простых игр. Вы приобретете необходимые навыки для разработки приложений на Python и узнаете, как их применять в реальной практике. Для лучшего усвоения материала в книге приведено множество примеров программного кода. В конце каждой главы вы найдете проект полноценной игры, иллюстрирующий ключевые идеи изложенной темы, а также краткое резюме пройденного материала и задачи для самопроверки. Прочитав эту книгу, вы всесторонне ознакомитесь с языком Python, усвоите базовые принципы программирования и будете готовы перенести их на почву других языков, за изучение которых возьметесь. Научитесь программировать на Python играючи.

Practical time series analysis: master time series data processing, visualization, and modeling using Python Avishek Pal, PKS Prakash (2017) Time Series Analysis allows us to analyze data which is generated over a period of time and has sequential interdependencies between the observations. This book describes special mathematical tricks and techniques which are geared towards exploring the internal structures of time series data and generating powerful descriptive and predictive insights. Also, the book is full of real-life examples of time series and their analyses using cutting-edge solutions developed in Python.

Глубокое обучение. Погружение в мир нейронных сетей С. Николенко, А. Кадурин, Е. Архангельская (2018) Перед вами - первая книга о глубоком обучении, написанная на русском языке. Глубокие модели оказались ключом, который подходит ко всем замкам сразу: новые архитектуры и алгоритмы обучения, а также увеличившиеся вычислительные мощности и появившиеся огромные наборы данных, привели к революционным прорывам в компьютерном зрении, распознавании речи, обработке естественного языка и многих других типично "человеческих" задачах машинного обучения.