Big data
Bharvi Dixit
With constantly evolving and growing datasets, organizations have the need to find actionable insights for their business. ElasticSearch, which is the world's most advanced search and analytics engine, brings the ability to make massive amounts of data usable in a matter of milliseconds. It not only gives you the power to build blazing fast search solutions over a massive amount of data, but can also serve as a NoSQL data store.This guide will take you on a tour to become a competent developer quickly with a solid knowledge level and understanding of the ElasticSearch core concepts. Starting from the beginning, this book will cover these core concepts, setting up ElasticSearch and various plugins, working with analyzers, and creating mappings. This book provides complete coverage of working with ElasticSearch using Python and performing CRUD operations and aggregation-based analytics, handling document relationships in the NoSQL world, working with geospatial data, and taking data backups. Finally, we’ll show you how to set up and scale ElasticSearch clusters in production environments as well as providing some best practices.
Marek Rogozinski, Rafal Kuc
ElasticSearch is a very fast and scalable open source search engine, designed with distribution and cloud in mind, complete with all the goodies that Apache Lucene has to offer. ElasticSearch’s schema-free architecture allows developers to index and search unstructured content, making it perfectly suited for both small projects and large big data warehouses, even those with petabytes of unstructured data.This book will guide you through the world of the most commonly used ElasticSearch server functionalities. You’ll start off by getting an understanding of the basics of ElasticSearch and its data indexing functionality. Next, you will see the querying capabilities of ElasticSearch, followed by a through explanation of scoring and search relevance. After this, you will explore the aggregation and data analysis capabilities of ElasticSearch and will learn how cluster administration and scaling can be used to boost your application performance. You’ll find out how to use the friendly REST APIs and how to tune ElasticSearch to make the most of it. By the end of this book, you will have be able to create amazing search solutions as per your project’s specifications.
Emotional Intelligence for IT Professionals. The must-have guide for a successful career in IT
Emília M. Ludovino
This book will help you discover your emotional quotient (EQ) through practices and techniques that are used by the most successful IT people in the world. It will make you familiar with the core skills of Emotional Intelligence, such as understanding the role that emotions play in life, especially in the workplace. You will learn to identify the factors that make your behavior consistent, not just to other employees, but to yourself. This includes recognizing, harnessing, predicting, fostering, valuing, soothing, increasing, decreasing, managing, shifting, influencing or turning around emotions and integrating accurate emotional information into decision-making, reasoning, problem solving, etc., because, emotions run business in a way that spreadsheets and logic cannot. When a deadline lurks, you’ll know the steps you need to take to keep calm and composed. You’ll find out how to meet the deadline, and not get bogged down by stress. We’ll explain these factors and techniques through real-life examples faced by IT employees and you’ll learn using the choices that they made. This book will give you a detailed analysis of the events and behavioral pattern of the employees during that time. This will help you improve your own EQ to the extent that you don’t just survive, but thrive in a competitive IT industry.
Nicolae Tarla
Power Virtual Agents is a set of technologies released under the Power Platform umbrella by Microsoft. It allows non-developers to create solutions to automate customer interactions and provide services using a conversational interface, thus relieving the pressure on front-line staff providing this kind of support.Empowering Organizations with Power Virtual Agents is a guide to building chatbots that can be deployed to handle front desk services without having to write code. The book takes a scenario-based approach to implementing bot services and automation to serve employees in the organization and external customers. You will uncover the features available in Power Virtual Agents for creating bots that can be integrated into an organization’s public site as well as specific web pages. Next, you will understand how to build bots and integrate them within the Teams environment for internal users. As you progress, you will explore complete examples for implementing automated agents (bots) that can be deployed on sites for interacting with external customers.By the end of this Power Virtual Agents chatbot book, you will have implemented several scenarios to serve external client requests for information, created scenarios to help internal users retrieve relevant information, and processed these in an automated conversational manner.
Emmanuel Raj
Engineering MLps presents comprehensive insights into MLOps coupled with real-world examples in Azure to help you to write programs, train robust and scalable ML models, and build ML pipelines to train and deploy models securely in production.The book begins by familiarizing you with the MLOps workflow so you can start writing programs to train ML models. Then you’ll then move on to explore options for serializing and packaging ML models post-training to deploy them to facilitate machine learning inference, model interoperability, and end-to-end model traceability. You’ll learn how to build ML pipelines, continuous integration and continuous delivery (CI/CD) pipelines, and monitor pipelines to systematically build, deploy, monitor, and govern ML solutions for businesses and industries. Finally, you’ll apply the knowledge you’ve gained to build real-world projects.By the end of this ML book, you'll have a 360-degree view of MLOps and be ready to implement MLOps in your organization.
Matt Benatan, Jochem Gietema, Marian Schneider
Deep learning has an increasingly significant impact on our lives, from suggesting content to playing a key role in mission- and safety-critical applications. As the influence of these algorithms grows, so does the concern for the safety and robustness of the systems which rely on them. Simply put, typical deep learning methods do not know when they don’t know.The field of Bayesian Deep Learning contains a range of methods for approximate Bayesian inference with deep networks. These methods help to improve the robustness of deep learning systems as they tell us how confident they are in their predictions, allowing us to take more in how we incorporate model predictions within our applications.Through this book, you will be introduced to the rapidly growing field of uncertainty-aware deep learning, developing an understanding of the importance of uncertainty estimation in robust machine learning systems. You will learn about a variety of popular Bayesian Deep Learning methods, and how to implement these through practical Python examples covering a range of application scenarios.By the end of the book, you will have a good understanding of Bayesian Deep Learning and its advantages, and you will be able to develop Bayesian Deep Learning models for safer, more robust deep learning systems.
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.
Ryan Doan
The rapid advancements in large language models (LLMs) bring significant challenges in deployment, maintenance, and scalability. This Essential Guide to LLMOps provides practical solutions and strategies to overcome these challenges, ensuring seamless integration and the optimization of LLMs in real-world applications.This book takes you through the historical background, core concepts, and essential tools for data analysis, model development, deployment, maintenance, and governance. You’ll learn how to streamline workflows, enhance efficiency in LLMOps processes, employ LLMOps tools for precise model fine-tuning, and address the critical aspects of model review and governance. You’ll also get to grips with the practices and performance considerations that are necessary for the responsible development and deployment of LLMs. The book equips you with insights into model inference, scalability, and continuous improvement, and shows you how to implement these in real-world applications.By the end of this book, you’ll have learned the nuances of LLMOps, including effective deployment strategies, scalability solutions, and continuous improvement techniques, equipping you to stay ahead in the dynamic world of AI.
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.
Sreeram Nudurupati
Apache Spark is a unified data analytics engine designed to process huge volumes of data quickly and efficiently. PySpark is Apache Spark's Python language API, which offers Python developers an easy-to-use scalable data analytics framework.Essential PySpark for Scalable Data Analytics starts by exploring the distributed computing paradigm and provides a high-level overview of Apache Spark. You'll begin your analytics journey with the data engineering process, learning how to perform data ingestion, cleansing, and integration at scale. This book helps you build real-time analytics pipelines that help you gain insights faster. You'll then discover methods for building cloud-based data lakes, and explore Delta Lake, which brings reliability to data lakes. The book also covers Data Lakehouse, an emerging paradigm, which combines the structure and performance of a data warehouse with the scalability of cloud-based data lakes. Later, you'll perform scalable data science and machine learning tasks using PySpark, such as data preparation, feature engineering, and model training and productionization. Finally, you'll learn ways to scale out standard Python ML libraries along with a new pandas API on top of PySpark called Koalas.By the end of this PySpark book, you'll be able to harness the power of PySpark to solve business problems.
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.
Ethereum Projects for Beginners. Build blockchain-based cryptocurrencies, smart contracts, and DApps
Kenny Vaneetvelde
Ethereum enables the development of efficient, smart contracts that contain code. These smart contracts can interact with other smart contracts to make decisions, store data, and send Ether to others.Ethereum Projects for Beginners provides you with a clear introduction to creating cryptocurrencies, smart contracts, and decentralized applications. As you make your way through the book, you’ll get to grips with detailed step-by-step processes to build advanced Ethereum projects. Each project will teach you enough about Ethereum to be productive right away. You will learn how tokenization works, think in a decentralized way, and build blockchain-based distributed computing systems. Towards the end of the book, you will develop interesting Ethereum projects such as creating wallets and secure data sharing.By the end of this book, you will be able to tackle blockchain challenges by implementing end-to-end projects using the full power of the Ethereum blockchain.
Mayukh Mukhopadhyay
Ethereum is a public, blockchain-based distributed computing platform featuring smart contract functionality. This book is your one-stop guide to blockchain and Ethereum smart contract development. We start by introducing you to the basics of blockchain. You'll learn about hash functions, Merkle trees, forking, mining, and much more. Then you'll learn about Ethereum and smart contracts, and we'll cover Ethereum virtual machine (EVM) in detail. Next, you'll get acquainted with DApps and DAOs and see how they work. We'll also delve into the mechanisms of advanced smart contracts, taking a practical approach.You'll also learn how to develop your own cryptocurrency from scratch in order to understand the business behind ICO. Further on, you'll get to know the key concepts of the Solidity programming language, enabling you to build decentralized blockchain-based applications. We'll also look at enterprise use cases, where you'll build a decentralized microblogging site. At the end of this book, we discuss blockchain-as-a-service, the dark web marketplace, and various advanced topics so you can get well versed with the blockchain principles and ecosystem.
EU General Data Protection Regulation (GDPR). An implementation and compliance guide
IT Governance Publishing, IT Governance Privacy Team
This book provides a thorough exploration of the EU General Data Protection Regulation (GDPR). It starts with the core principles of GDPR, explaining its purpose, key concepts, and how it impacts data controllers and processors. The book covers essential features like data subject rights, data processing principles, and privacy compliance frameworks. It also explores the role of the Data Protection Officer (DPO) and the importance of conducting data protection impact assessments (DPIAs).Focusing on practical implementation, the book highlights the need for robust information security measures to meet GDPR standards. It provides actionable advice on best practices, including managing data breaches, ensuring lawful consent, and processing subject access requests. The guide also addresses the complexities of international data transfers in line with GDPR requirements.Finally, the book outlines GDPR enforcement mechanisms, detailing the powers of supervisory authorities and the steps to demonstrate compliance. This resource offers organizations a comprehensive roadmap to align with GDPR, laying the groundwork for effective data protection and compliance.
Excel 2010 PL. Ilustrowany przewodnik
Krzysztof Masłowski
Pobierz dodatkowy rozdział do książki! Skalkuluj sobie awans z nowym Excelem 2010! Podstawowe zasady obsługi programu, czyli od czego zacząć przygodę z Excelem Proste operacje i trudne obliczenia, czyli do czego może przydać się ta aplikacja Wykresy, drukowanie i analiza danych, czyli jak wykorzystać ogrom możliwości Excel 2010, podobnie jak każda kolejna wersja tego niezwykle popularnego programu, oferuje swoim użytkownikom nowe, ciekawe możliwości. Zarówno tak zwany przeciętny użytkownik, jak i analityk finansowy znajdą tu praktyczne funkcje, ułatwiające im codzienną pracę. Do najbardziej nowatorskich pomysłów należy opcja Wykresy przebiegu w czasie, umożliwiająca tworzenie miniwykresów, zajmujących jedną komórkę. Aplikacja zawiera też wyspecjalizowane narzędzia do analizy danych oraz lepsze filtry, zapewnia wyższy komfort przy pracy zespołowej i współdzieleniu arkuszy, a dzięki dużej wydajności pozwala zaoszczędzić sporo czasu. "Excel 2010 PL. Ilustrowany przewodnik " to przejrzysty, intuicyjnie napisany podręcznik, gwarantujący Ci szybkie i bezproblemowe zapoznanie się z dostępnymi narzędziami oraz sposobem działania programu. Z pomocą tej książki bez trudu opanujesz nowy interfejs użytkownika i dostosujesz go do własnych potrzeb, a także poznasz sekrety i sztuczki związane z podstawowymi oraz zaawansowanymi metodami obróbki danych liczbowych. Krok po kroku nauczysz się sprawnie korzystać z Excela: dowiesz się m.in., jak stworzyć listę płac albo rozliczyć delegację, a ponadto poznasz mnóstwo innych praktycznych jego zastosowań. Każde kolejne działanie — od najprostszych po najbardziej skomplikowane — zostało tu szczegółowo opisane i zilustrowane zrzutem ekranu. Wstążka i okno programu — zmiana wyglądu i kolorystyki Skróty klawiszowe, prezentacja arkusza i skoroszytu Poruszanie się po arkuszu i między arkuszami Wprowadzanie danych do komórek i edycja tych danych Zakresy Wstawianie i usuwanie kolumn, wierszy, komórek Nazywanie skoroszytów i arkuszy oraz działania na kilku arkuszach Kopiowanie, dodawanie i usuwanie arkuszy Oglądanie i ukrywanie arkuszy oraz tryby ich wyświetlania Operatory używane w formułach i kolejność ich działania Adresy względne, mieszane, bezwzględne i trójwymiarowe Formatowanie zmieniające znaczenie, warunkowe i niestandardowe Tworzenie i przekształcanie wykresów oraz ich różne typy Podgląd, drukowanie i układ strony Elementy analizy danych — sortowanie, filtrowanie Oto bogato ilustrowany przewodnik po świecie możliwości Excela!
Witold Wrotek
Z Excelem się kalkuluje! Automatyzacja pracy Wprowadzanie i edycja danych Tworzenie wykresów i drukowanie arkuszy Stosowanie formuł i funkcji obliczeniowych Umiesz liczyć - licz z Excelem! Czym jest arkusz kalkulacyjny Excela? To doskonałe narzędzie ze stajni Microsoft Office jest odpowiedzią na tony zeszytów wraz z tabelami, pomyłki popełniane przy liczeniu, kalkulatory z ograniczoną liczbą funkcji czy wykresy rysowane kredą na tablicach. Excel to prawdopodobnie najlepszy arkusz kalkulacyjny na świecie. Odnosi on sukcesy od roku 1987 i doskonale sprawdza się w przedsiębiorstwach, szkołach i na osobistych pecetach. Z jego pomocą można zautomatyzować prace administracyjne, oszacować koszty, stworzyć symulacje, wygenerować wykresy czy kontrolować budżet - firmowy i domowy. A jak Ty planujesz wykorzystać dziesiątki funkcji i możliwości tego narzędzia? Najczęstszym problemem podczas pracy z Excelem jest wydobycie tkwiącej w nim mocy obliczeniowej. Dlatego też umiejętność jego obsługi jest tak pożądana przez pracodawców i przynosi firmie wymierne korzyści. Z tym podręcznikiem zaczniesz bezbłędnie wykonywać obliczenia w arkuszach Excela, będziesz formatować komórki i gromadzić dane. Przestaniesz bać się tworzenia wykresów, używania funkcji i formuł oraz poruszania się między skoroszytami. Skorzystasz z ilustracji, obrazowych przykładów i ćwiczeń - bez konieczności wgryzania się w specjalistyczną terminologię. Obierz kurs na Excel! Tworzenie nowych i otwieranie istniejących arkuszy Korzystanie z funkcji i formuł matematycznych, finansowych, statystycznych i innych Wprowadzanie do komórek, formatowanie oraz wyszukiwanie danych Drukowanie arkuszy Tworzenie wykresów Praca z Analysis ToolPak