Python
Aivars Kalvans
Despite being developed in the 1980s, Oracle Tuxedo still runs a significant part of critical infrastructure and is not going away any time soon. Modernizing Oracle Tuxedo Applications with Python will help you get to grips with the most important Tuxedo concepts by writing Python code.The book starts with an introduction to Oracle Tuxedo and guides you in installing its latest version and Python bindings for Tuxedo on Linux. You'll then learn how to build your first server and client, configure Tuxedo, and start running an application. As you advance, you'll understand load balancing and work with the BBL server, which is at the heart of a Tuxedo application. This Tuxedo book will also cover Boolean expressions and different ways to export Tuxedo buffers for storage and transmission, before showing you how to implement servers and clients and use the management information base to change the configuration dynamically. Once you've learned how to configure Tuxedo for transactions and control them in application code, you'll discover how to use the store-and-forward functionality to reach destinations and use an Oracle database from a Tuxedo application.By the end of this Oracle Tuxedo book, you'll be able to perform common Tuxedo programming tasks with Python and integrate Tuxedo applications with other parts of modern infrastructure.
Albert Lukaszewski
Python is a dynamic programming language, which is completely enterprise ready, owing largely to the variety of support modules that are available to extend its capabilities. In order to build productive and feature-rich Python applications, we need to use MySQL for Python, a module that provides database support to our applications. Although you might be familiar with accessing data in MySQL, here you will learn how to access data through MySQL for Python efficiently and effectively.This book demonstrates how to boost the productivity of your Python applications by integrating them with the MySQL database server, the world's most powerful open source database. It will teach you to access the data on your MySQL database server easily with Python's library for MySQL using a practical, hands-on approach. Leaving theory to the classroom, this book uses real-world code to solve real-world problems with real-world solutions.The book starts by exploring the various means of installing MySQL for Python on different platforms and how to use simple database querying techniques to improve your programs. It then takes you through data insertion, data retrieval, and error-handling techniques to create robust programs. The book also covers automation of both database and user creation, and administration of access controls. As the book progresses, you will learn to use many more advanced features of Python for MySQL that facilitate effective administration of your database through Python. Every chapter is illustrated with a project that you can deploy in your own situation.By the end of this book, you will know several techniques for interfacing your Python applications with MySQL effectively so that powerful database management through Python becomes easy to achieve and easy to maintain.
Myśl w języku Python! Nauka programowania. Wydanie II
Allen B. Downey
Aby stać się cenionym programistą, trzeba zacząć od bardzo solidnych podstaw. Python jest idealną propozycją dla osób, które chcą nauczyć się programowania. Składnia i podstawowe koncepcje programistyczne w Pythonie są dość proste do zrozumienia. Sam język ma duże możliwości zastosowania w różnych dziedzinach wiedzy. Umożliwia przy tym pisanie czytelnego i łatwego w konserwacji kodu, co jest ogromną zaletą. Trzymasz w ręku praktyczny przewodnik do nauki programowania. Znajdziesz w nim przystępnie napisane wyjaśnienia dotyczące podstawowych pojęć programistycznych. Dowiesz się, jak stosować funkcje, czym jest rekurencja, jak wyglądają struktury danych i na czym polega projektowanie obiektowe. W każdym rozdziale znalazły się praktyczne ćwiczenia, dzięki którym będziesz używać poznawanych koncepcji i utrwalisz zdobytą wiedzę. W tej książce: przedstawiono podstawy Pythona, w tym jego składnię i semantykę opisano najważniejsze koncepcje programistyczne i zdefiniowano istotne pojęcia pokazano, jak stosować wartości, zmienne, instrukcje, funkcje i struktury danych przedstawiono metody pracy z plikami i bazami danych wyjaśniono zagadnienia programowania obiektowego opisano techniki debugowania służące do usuwania błędów składniowych, uruchomieniowych i semantycznych Python: dzięki niemu zaczniesz myśleć jak informatyk!
Myśl w języku Python! Nauka programowania. Wydanie III
Allen B. Downey
Python to wspaniały język programowania. Jest wszechstronny, wyrazisty i zwięzły, pozwala też korzystać z rosnącej kolekcji narzędzi i bibliotek. Cenią go zarówno profesjonalni twórcy oprogramowania, jak i amatorzy czy osoby spoza branży, które w Pythonie widzą cenne narzędzie do tworzenia własnych aplikacji, znacząco poprawiających jakość i wydajność pracy. Wyjątkowy przewodnik dla osób zainteresowanych nauką programowania od podstaw! Luciano Ramalho, autor książki Zaawansowany Python To trzecie wydanie przejrzystego przewodnika, który ułatwi Ci naukę programowania w Pythonie. Zaczniesz od przyswojenia podstawowych pojęć programistycznych, aby wkrótce płynnie posługiwać się funkcjami i strukturami danych. Zdobędziesz też umiejętność programowania zorientowanego obiektowo. W tym zaktualizowanym wydaniu znajdziesz również wskazówki, dzięki którym zastosujesz duże modele językowe, takie jak ChatGPT, do nauki programowania. Dowiesz się, jak tworzyć skuteczne zapytania dla tych modeli, a także jak testować i debugować kod Pythona. Dzięki ćwiczeniom, zamieszczonym w każdym rozdziale, będziesz stopniowo szlifować umiejętności programistyczne, a zasugerowane w książce strategie pomogą Ci w unikaniu frustrujących błędów - w ten sposób szybko nauczysz się tworzyć poprawny kod. W książce: podstawy Pythona zmienne, instrukcje, funkcje i struktury danych praca z plikami i bazami danych obiekty, metody i programowanie zorientowane obiektowo obsługa błędów składniowych, wykonawczych i semantycznych użycie dużych modeli językowych do przyspieszenia nauki programowania Dzięki tej książce nauczysz się używać dużych modeli językowych do nauki programowania! Sam Lau, współautor książki Learning Data Science O książce: Eksperyment myślowy — recenzja książki
Bhargav Srinivasa-Desikan
Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data.This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy.You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning.This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis.
Sohom Ghosh, Dwight Gunning
If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems.You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots. By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language.
Mona M, Premkumar Rangarajan, Julien Simon
Natural language processing (NLP) uses machine learning to extract information from unstructured data. This book will help you to move quickly from business questions to high-performance models in production.To start with, you'll understand the importance of NLP in today’s business applications and learn the features of Amazon Comprehend and Amazon Textract to build NLP models using Python and Jupyter Notebooks. The book then shows you how to integrate AI in applications for accelerating business outcomes with just a few lines of code. Throughout the book, you'll cover use cases such as smart text search, setting up compliance and controls when processing confidential documents, real-time text analytics, and much more to understand various NLP scenarios. You'll deploy and monitor scalable NLP models in production for real-time and batch requirements. As you advance, you'll explore strategies for including humans in the loop for different purposes in a document processing workflow. Moreover, you'll learn best practices for auto-scaling your NLP inference for enterprise traffic.Whether you're new to ML or an experienced practitioner, by the end of this NLP book, you'll have the confidence to use AWS AI services to build powerful NLP applications.
Tadej Magajna
Flair is an easy-to-understand natural language processing (NLP) framework designed to facilitate training and distribution of state-of-the-art NLP models for named entity recognition, part-of-speech tagging, and text classification. Flair is also a text embedding library for combining different types of embeddings, such as document embeddings, Transformer embeddings, and the proposed Flair embeddings.Natural Language Processing with Flair takes a hands-on approach to explaining and solving real-world NLP problems. You'll begin by installing Flair and learning about the basic NLP concepts and terminology. You will explore Flair's extensive features, such as sequence tagging, text classification, and word embeddings, through practical exercises. As you advance, you will train your own sequence labeling and text classification models and learn how to use hyperparameter tuning in order to choose the right training parameters. You will learn about the idea behind one-shot and few-shot learning through a novel text classification technique TARS. Finally, you will solve several real-world NLP problems through hands-on exercises, as well as learn how to deploy Flair models to production.By the end of this Flair book, you'll have developed a thorough understanding of typical NLP problems and you’ll be able to solve them with Flair.