Python
Dipayan Sarkar, Vijayalakshmi Natarajan
Ensemble modeling is an approach used to improve the performance of machine learning models. It combines two or more similar or dissimilar machine learning algorithms to deliver superior intellectual powers. This book will help you to implement popular machine learning algorithms to cover different paradigms of ensemble machine learning such as boosting, bagging, and stacking.The Ensemble Machine Learning Cookbook will start by getting you acquainted with the basics of ensemble techniques and exploratory data analysis. You'll then learn to implement tasks related to statistical and machine learning algorithms to understand the ensemble of multiple heterogeneous algorithms. It will also ensure that you don't miss out on key topics, such as like resampling methods. As you progress, you’ll get a better understanding of bagging, boosting, stacking, and working with the Random Forest algorithm using real-world examples. The book will highlight how these ensemble methods use multiple models to improve machine learning results, as compared to a single model. In the concluding chapters, you'll delve into advanced ensemble models using neural networks, natural language processing, and more. You’ll also be able to implement models such as fraud detection, text categorization, and sentiment analysis.By the end of this book, you'll be able to harness ensemble techniques and the working mechanisms of machine learning algorithms to build intelligent models using individual recipes.
Enterprise DevOps for Architects. Leverage AIOps and DevSecOps for secure digital transformation
Jeroen Mulder
Digital transformation is the new paradigm in enterprises, but the big question remains: is the enterprise ready for transformation using native technology embedded in Agile/DevOps? With this book, you'll see how to design, implement, and integrate DevOps in the enterprise architecture while keeping the Ops team on board and remaining resilient. The focus of the book is not to introduce the hundreds of different tools that are available for implementing DevOps, but instead to show you how to create a successful DevOps architecture.This book provides an architectural overview of DevOps, AIOps, and DevSecOps – the three domains that drive and accelerate digital transformation. Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this DevOps book will help you to successfully integrate DevOps into enterprise architecture. You'll learn what AIOps is and what value it can bring to an enterprise. Lastly, you will learn how to integrate security principles such as zero-trust and industry security frameworks into DevOps with DevSecOps.By the end of this DevOps book, you'll be able to develop robust DevOps architectures, know which toolsets you can use for your DevOps implementation, and have a deeper understanding of next-level DevOps by implementing Site Reliability Engineering (SRE).
Leonard S. Woody III
Quantum computing is an exciting subject that offers hope to solve the world’s most complex problems at a quicker pace. It is being used quite widely in different spheres of technology, including cybersecurity, finance, and many more, but its concepts, such as superposition, are often misunderstood because engineers may not know the math to understand them. This book will teach the requisite math concepts in an intuitive way and connect them to principles in quantum computing.Starting with the most basic of concepts, 2D vectors that are just line segments in space, you'll move on to tackle matrix multiplication using an instinctive method. Linearity is the major theme throughout the book and since quantum mechanics is a linear theory, you'll see how they go hand in hand. As you advance, you'll understand intrinsically what a vector is and how to transform vectors with matrices and operators. You'll also see how complex numbers make their voices heard and understand the probability behind it all.It’s all here, in writing you can understand. This is not a stuffy math book with definitions, axioms, theorems, and so on. This book meets you where you’re at and guides you to where you need to be for quantum computing. Already know some of this stuff? No problem! The book is componentized, so you can learn just the parts you want. And with tons of exercises and their answers, you'll get all the practice you need.
Rongpeng Li
Statistics remain the backbone of modern analysis tasks, helping you to interpret the results produced by data science pipelines. This book is a detailed guide covering the math and various statistical methods required for undertaking data science tasks.The book starts by showing you how to preprocess data and inspect distributions and correlations from a statistical perspective. You’ll then get to grips with the fundamentals of statistical analysis and apply its concepts to real-world datasets. As you advance, you’ll find out how statistical concepts emerge from different stages of data science pipelines, understand the summary of datasets in the language of statistics, and use it to build a solid foundation for robust data products such as explanatory models and predictive models. Once you’ve uncovered the working mechanism of data science algorithms, you’ll cover essential concepts for efficient data collection, cleaning, mining, visualization, and analysis. Finally, you’ll implement statistical methods in key machine learning tasks such as classification, regression, tree-based methods, and ensemble learning.By the end of this Essential Statistics for Non-STEM Data Analysts book, you’ll have learned how to build and present a self-contained, statistics-backed data product to meet your business goals.
Christian Cote, Matija Lah, Madina Saitakhmetova
ETL is one of the most common and tedious procedures for moving and processing data from one database to another. With the help of this book, you will be able to speed up the process by designing effective ETL solutions using the Azure services available for handling and transforming any data to suit your requirements.With this cookbook, you’ll become well versed in all the features of SQL Server Integration Services (SSIS) to perform data migration and ETL tasks that integrate with Azure. You’ll learn how to transform data in Azure and understand how legacy systems perform ETL on-premises using SSIS. Later chapters will get you up to speed with connecting and retrieving data from SQL Server 2019 Big Data Clusters, and even show you how to extend and customize the SSIS toolbox using custom-developed tasks and transforms. This ETL book also contains practical recipes for moving and transforming data with Azure services, such as Data Factory and Azure Databricks, and lets you explore various options for migrating SSIS packages to Azure. Toward the end, you’ll find out how to profile data in the cloud and automate service creation with Business Intelligence Markup Language (BIML).By the end of this book, you’ll have developed the skills you need to create and automate ETL solutions on-premises as well as in Azure.
Michał Jaworski, Tarek Ziadé
Python is a dynamic programming language that's used in a wide range of domains thanks to its simple yet powerful nature. Although writing Python code is easy, making it readable, reusable, and easy to maintain is challenging. Complete with best practices, useful tools, and standards implemented by professional Python developers, the third edition of Expert Python Programming will help you overcome this challenge.The book will start by taking you through the new features in Python 3.7. You'll then learn the advanced components of Python syntax, in addition to understanding how to apply concepts of various programming paradigms, including object-oriented programming, functional programming, and event-driven programming. This book will also guide you through learning the naming best practices, writing your own distributable Python packages, and getting up to speed with automated ways to deploy your software on remote servers. You’ll discover how to create useful Python extensions with C, C++, Cython, and CFFI. Furthermore, studying about code management tools, writing clear documentation, and exploring test-driven development will help you write clean code.By the end of the book, you will have become an expert in writing efficient and maintainable Python code.
Michał Jaworski, Tarek Ziade, Tarek Ziadé
This new edition of Expert Python Programming provides you with a thorough understanding of the process of building and maintaining Python apps. Complete with best practices, useful tools, and standards implemented by professional Python developers, this fourth edition has been extensively updated. Throughout this book, you’ll get acquainted with the latest Python improvements, syntax elements, and interesting tools to boost your development efficiency.The initial few chapters will allow experienced programmers coming from different languages to transition to the Python ecosystem. You will explore common software design patterns and various programming methodologies, such as event-driven programming, concurrency, and metaprogramming. You will also go through complex code examples and try to solve meaningful problems by bridging Python with C and C++, writing extensions that benefit from the strengths of multiple languages. Finally, you will understand the complete lifetime of any application after it goes live, including packaging and testing automation.By the end of this book, you will have gained actionable Python programming insights that will help you effectively solve challenging problems.
Exploring GPT-3. An unofficial first look at the general-purpose language processing API from OpenAI
Steve Tingiris
Generative Pre-trained Transformer 3 (GPT-3) is a highly advanced language model from OpenAI that can generate written text that is virtually indistinguishable from text written by humans. Whether you have a technical or non-technical background, this book will help you understand and start working with GPT-3 and the OpenAI API.If you want to get hands-on with leveraging artificial intelligence for natural language processing (NLP) tasks, this easy-to-follow book will help you get started. Beginning with a high-level introduction to NLP and GPT-3, the book takes you through practical examples that show how to leverage the OpenAI API and GPT-3 for text generation, classification, and semantic search. You'll explore the capabilities of the OpenAI API and GPT-3 and find out which NLP use cases GPT-3 is best suited for. You’ll also learn how to use the API and optimize requests for the best possible results. With examples focusing on the OpenAI Playground and easy-to-follow JavaScript and Python code samples, the book illustrates the possible applications of GPT-3 in production.By the end of this book, you'll understand the best use cases for GPT-3 and how to integrate the OpenAI API in your applications for a wide array of NLP tasks.
Omar Khedher
OpenStack is a very popular cloud computing platform that has enabled several organizations during the last few years to successfully implement their Infrastructure as a Service (IaaS) platforms. This book will guide you through new features of the latest OpenStack releases and how to bring them into production straightaway in an agile way.It starts by showing you how to expand your current OpenStack setup and how to approach your next OpenStack Data Center generation deployment. You will discover how to extend your storage and network capacity and also take advantage of containerization technology such as Docker and Kubernetes in OpenStack. Additionally, you'll explore the power of big data as a Service terminology implemented in OpenStack by integrating the Sahara project. This book will teach you how to build Hadoop clusters and launch jobs in a very simple way. Then you'll automate and deploy applications on top of OpenStack. You will discover how to write your own plugin in the Murano project. The final part of the book will go through best practices for security such as identity, access management, and authentication exposed by Keystone in OpenStack. By the end of this book, you will be ready to extend and customize your private cloud based on your requirements.
Luca Zavarella
Python and R allow you to extend Power BI capabilities to simplify ingestion and transformation activities, enhance dashboards, and highlight insights. With this book, you'll be able to make your artifacts far more interesting and rich in insights using analytical languages.You'll start by learning how to configure your Power BI environment to use your Python and R scripts. The book then explores data ingestion and data transformation extensions, and advances to focus on data augmentation and data visualization. You'll understand how to import data from external sources and transform them using complex algorithms. The book helps you implement personal data de-identification methods such as pseudonymization, anonymization, and masking in Power BI. You'll be able to call external APIs to enrich your data much more quickly using Python programming and R programming. Later, you'll learn advanced Python and R techniques to perform in-depth analysis and extract valuable information using statistics and machine learning. You'll also understand the main statistical features of datasets by plotting multiple visual graphs in the process of creating a machine learning model.By the end of this book, you’ll be able to enrich your Power BI data models and visualizations using complex algorithms in Python and R.
Luca Zavarella, Rajat Talwar
The latest edition of this book delves deep into advanced analytics, focusing on enhancing Python and R proficiency within Power BI. New chapters cover optimizing Python and R settings, utilizing Intel's Math Kernel Library (MKL) for performance boosts, and addressing integration challenges. Techniques for managing large datasets beyond available RAM, employing the Parquet data format, and advanced fuzzy matching algorithms are explored. Additionally, it discusses leveraging SQL Server Language Extensions to overcome traditional Python and R limitations in Power BI. It also helps in crafting sophisticated visualizations using the Grammar of Graphics in both R and Python.This Power BI book will help you master data validation with regular expressions, import data from diverse sources, and apply advanced algorithms for transformation. You'll learn how to safeguard personal data in Power BI with techniques like pseudonymization, anonymization, and data masking. You'll also get to grips with the key statistical features of datasets by plotting multiple visual graphs in the process of building a machine learning model. The book will guide you on utilizing external APIs for enrichment, enhancing I/O performance, and leveraging Python and R for analysis.You'll reinforce your learning with questions at the end of each chapter.
Cuantum Technologies LLC
Feature engineering is essential for building robust predictive models. This book delves into practical techniques for transforming raw data into powerful features using Scikit-Learn. You'll explore automation, deep learning integrations, and advanced topics like feature selection and model evaluation. Learn to handle real-world data challenges, enhance accuracy, and streamline your workflows.Through hands-on projects, readers will gain practical experience with techniques such as clustering, pipelines, and feature selection, applied to domains like retail and healthcare. Step-by-step instructions ensure a comprehensive learning journey, from foundational concepts to advanced automation and hybrid modeling approaches.By combining theory with real-world applications, the book equips data professionals with the tools to unlock the full potential of machine learning models. Whether working with structured datasets or integrating deep learning features, this guide provides actionable insights to tackle any data transformation challenge effectively.
Finanse i Python. Łagodne wprowadzenie do teorii finansów
Yves Hilpisch
Finanse i Python. Łagodne wprowadzenie do teorii finansów Rozwój technologii i dostęp do danych finansowych stały się ogromnym ułatwieniem w korzystaniu z globalnych rynków finansowych. Jeśli zechcesz, możesz szybko zacząć przygodę na przykład z handlem algorytmicznym. Wystarczy, że masz niewielkie pojęcie o matematyce, programowaniu i ekonomii. Niestety, nieliczne programy nauczania o finansach integrują ze sobą te trzy dziedziny. Tymczasem koncepcje matematyczne wspaniale ułatwiają zrozumienie pojęć z zakresu inżynierii finansowej, a wczesne włączanie ćwiczeń programistycznych pozwala na znaczne zwiększenie efektywności takiej edukacji. Dzięki tej praktycznej, przystępnie napisanej książce szybko zrozumiesz podstawy teorii finansów, modelowania danych finansowych i zastosowania Pythona w finansach obliczeniowych. Znajdziesz tu systematyczne wprowadzenie do inżynierii finansowej, handlu algorytmicznego czy zarządzania aktywami. Zdobędziesz umiejętności tworzenia w Pythonie programów, które ułatwią Ci rozwiązywanie takich problemów jak ustalanie składu portfeli inwestycyjnych zgodnie z nowoczesną teorią portfela, a także wycena opcji i innych instrumentów pochodnych. Jeśli zajmujesz stanowisko kierownicze w branży finansowej, z pewnością przyda Ci się wiedza o zastosowaniu Pythona w finansach. Jeśli już biegle kodujesz w Pythonie, łatwiej skorzystasz ze swoich umiejętności w tworzeniu przydatnych aplikacji z zakresu inżynierii finansowej. W książce między innymi: matematyczne podstawy teorii finansów i programowania w Pythonie modele ekonomiczne i modelowanie danych finansowych zastosowanie Pythona w obliczeniach związanych z finansami wycena, podejmowanie decyzji, równowaga i alokacja aktywów zastosowanie bibliotek i narzędzi Pythona w modelowaniu finansowym Teoria finansów? Z Pythonem to dziecinnie proste!
Joel Perras
Flask is a small but powerful web development framework for Python. Though Flask is termed a micro-framework, it is no way lacking in functionality; there are many extensions available to Flask which helps it to function at the same level as other large frameworks such as Django and Ruby on Rails.This book will demonstrate how to develop a series of web application projects with the Python web micro-framework, and leverage extensions and external Python libraries and APIs to extend the development of a variety of larger and more complex web applications.The book will start by explaining Python’s Virtualenv library and how to create and switch between multiple virtual environments. You’ll first build an SQL database-backed application, which will use Flask-WTF, Flask-SQLAlchemy, Jinja templates, and other methods. Next you’ll move on to a timeline application, built using concepts including pytest-Flask, the Blinker package, data modelling for user timelines, exception handling, and creating and organizing CLI tools.Moving on, you’ll discover how to implement a photo timeline application where you’ll explore topics such as writing and running celery tasks, API error handling and testing, and Werkzeug middlewares.Finally, the book walks you through creating an application which fetches data from GitHub and stores it locally. You will also learn how to install and configure Flask-Click extension.
Shalabh Aggarwal
If you are a web developer who wants to learn more about developing applications in Flask and scale them with industry-standard practices, this is the book for you. This book will also act as a handy tool if you are aware of Flask's major extensions and want to make the best use of them.It is assumed that you have knowledge of Python and a basic understanding of Flask. If you are completely new to Flask, reading the book from the first chapter and going forward will help in getting acquainted with Flask as you go ahead.
Shalabh Aggarwal
Flask, the lightweight Python web framework, is popular thanks to its powerful modular design that lets you build scalable web apps. With this recipe-based guide, you’ll explore modern solutions and best practices for Flask web development.Updated to the latest version of Flask and Python 3, this second edition of Flask Framework Cookbook moves away from some of the old and obsolete libraries and introduces new recipes on cutting-edge technologies. You’ll discover different ways of using Flask to create, deploy, and manage microservices. This Flask Python book starts by covering the different configurations that a Flask application can make use of, and then helps you work with templates and learn about the ORM and view layers. You’ll also be able to write an admin interface and get to grips with debugging and logging errors. Finally, you’ll learn a variety of deployment and post-deployment techniques for platforms such as Apache, Tornado, and Heroku.By the end of this book, you’ll have gained all the knowledge you need to confidently write Flask applications and scale them using standard industry practices.