Azure Machine Learning Engineering. Deploy, fine-tune, and optimize ML models using Microsoft Azure

Sina Fakhraee, Balamurugan Balakreshnan, Megan Masanz

Data scientists working on productionizing machine learning (ML) workloads face a breadth of challenges at every step owing to the countless factors involved in getting ML models deployed and running. This book offers solutions to common issues, detailed explanations of essential concepts, and step-by-step instructions to productionize ML workloads using the Azure Machine Learning service. You’ll see how data scientists and ML engineers working with Microsoft Azure can train and deploy ML models at scale by putting their knowledge to work with this practical guide.Throughout the book, you’ll learn how to train, register, and productionize ML models by making use of the power of the Azure Machine Learning service. You’ll get to grips with scoring models in real time and batch, explaining models to earn business trust, mitigating model bias, and developing solutions using an MLOps framework.By the end of this Azure Machine Learning book, you’ll be ready to build and deploy end-to-end ML solutions into a production system using the Azure Machine Learning service for real-time scenarios.

Badanie danych. Raport z pierwszej linii działań

Rachel Schutt, Cathy O'Neil

Unikalne wprowadzenie do nauki o danych! W dzisiejszych czasach najcenniejszym dobrem jest informacja. Ogromne ilości danych są przechowywane w przepastnych bazach danych, a kluczem do sukcesu jest ich umiejętna analiza i wyciąganie wniosków. To dynamicznie rozwijająca się dziedzina wiedzy, w której do tej pory brakowało solidnych podręczników, pozwalających na dogłębne poznanie tego obszaru. Na szczęście to się zmieniło! To unikalna książka, w której badacze z największych firm branży IT dzielą się skutecznymi technikami analizy danych. Z kolejnych rozdziałów dowiesz się, czym jest nauka o danych, model danych oraz test A/B. Ponadto zdobędziesz wiedzę na temat wnioskowania statystycznego, algorytmów, języka R oraz wizualizacji danych. Sięgnij po tę książkę, jeżeli chcesz się dowiedzieć, jak wykrywać oszustwa, korzystać z MapReduce oraz badać przyczynowość. To obowiązkowa pozycja na półce czytelników zainteresowanych badaniem danych. Wśród tematów poruszonych w książce odnajdziesz: Wnioskowanie statystyczne, eksploracyjną analizę danych i proces (metodologię) nauki o danych Algorytmy Filtry spamu, naiwny algorytm Bayesa i wstępną obróbkę danych Regresję logistyczną Modelowanie finansowe Mechanizmy rekomendacji i przyczynowość Wizualizowanie danych Sieci społecznościowe i dziennikarstwo danych Inżynierię danych, systemy MapReduce, Pregel i Hadoop Wyciągnij wartościowe wnioski z posiadanych informacji!

Bayesian Analysis with Python. Click here to enter text

Osvaldo Martin

The purpose of this book is to teach the main concepts of Bayesian data analysis. We will learn how to effectively use PyMC3, a Python library for probabilistic programming, to perform Bayesian parameter estimation, to check models and validate them. This book begins presenting the key concepts of the Bayesian framework and the main advantages of this approach from a practical point of view. Moving on, we will explore the power and flexibility of generalized linear models and how to adapt them to a wide array of problems, including regression and classification. We will also look into mixture models and clustering data, and we will finish with advanced topics like non-parametrics models and Gaussian processes. With the help of Python and PyMC3 you will learn to implement, check and expand Bayesian models to solve data analysis problems.

Bazy danych. Pierwsze starcie

Adam Pelikant

Zobacz, jakie to proste -- naucz się tworzyć bazy danych! Jak tworzyć formularze i raporty? Jak modyfikować strukturę tabel? Jak stosować mechanizmy wymiany danych? Współczesny świat wymusza na przedsiębiorstwach gromadzenie oraz przetwarzanie ogromnej ilości informacji. To sprawia, że muszą one dysponować wydajnymi i sprawnymi bazami danych. Aby zbudować taki system zarządzania danymi, niezbędne są odpowiednie narzędzia -- jednym z nich jest program MS Access. Ta aplikacja przede wszystkim pozwala na łatwą kontrolę poprawności tworzonych projektów oraz zapewnia integrację narzędzi służących do tworzenia struktury relacyjnej. Dba także o zgodność tych narzędzi ze standardem języka zapytań SQL, wykorzystywanym do tworzenia i modyfikowania baz danych oraz operowania na zgromadzonych w nich informacjach. Książka "Bazy danych. Pierwsze starcie" stanowi doskonałe wprowadzenie w tematykę tworzenia baz danych. Zawiera wszystkie potrzebne informacje, podane w prosty i przejrzysty sposób. Ten podręcznik przyda się zarówno studentom kierunków informatycznych, jak i wszystkim tym, którzy chcą zdobyć wiedzę o nowoczesnych metodach budowania takich baz. Stąd dowiesz się m.in., jak wykorzystywać język zapytań SQL, w jaki sposób tworzyć tabele, formularze i raporty oraz stosować mechanizmy wymiany danych, a także na czym polega filtrowanie i sortowanie w zapytaniach. Zdobędziesz wiedzę i umiejętności wystarczające do samodzielnego zbudowania wydajnej bazy danych i sprawnego nią zarządzania. Projektowanie bazy danych -- narzędzia wizualne Tworzenie formularzy i raportów Strukturalny język zapytań SQL w wersji MS JetSQL Składnia podstawowa Unia -- koniunkcja zbiorów Grupowanie i funkcje agregujące Zastosowanie języka SQL z poziomu formularzy Mechanizmy wymiany danych Obiekty: DAO, RDO, ADO Zastosowanie mechanizmów wymiany danych przy tworzeniu aplikacji Stwórz własną, niezawodną bazę danych!

Bazy danych. Podstawy projektowania i języka SQL

Krystyna Czapla

Idealna baza danych — szyta na Twoją miarę! Faza projektu, czyli jak opracować tabele i określić zależności między nimi Faza implementacji, czyli jak przejść od projektu do tworzenia fizycznej bazy Faza trzecia, czyli jak czerpać informacje z bazy danych w nowoczesnych aplikacjach Bazy danych są dziś tworzone na potęgę i wykorzystywane niemal na każdym kroku. Od czasu pojawienia się komputerów osobistych, internetu i potężnych serwerów ilość danych wymagających zapisania i przetworzenia wciąż wzrasta, a ich sensowne posegregowanie, zapewnienie integralności, łatwości przeszukiwania i możliwości analizowania to umiejętność na wagę złota. Jeśli chcesz ją zdobyć lub udoskonalić, ta książka na pewno Ci w tym pomoże. Znajdziesz tu klarowne, jasne informacje dotyczące kolejnych etapów projektowania oraz implementacji bazy danych, z podziałem na dwie odrębne metody — modelowanie i normalizację. Poznasz obszerne podstawy języka SQL — pojęcia, typy danych, składnię i całe zestawy poleceń — i na konkretnych przykładach zobaczysz, jak używać tego języka. Zrozumiesz też, do czego służy język zapytań i co można zrobić przy użyciu języka DML. To pozwoli Ci z łatwością wykonać ćwiczenia utrwalające, a gdy skończysz będziesz gotowy zmierzyć się z budową własnej bazy! Modelowanie logiczne Normalizacja danych Język baz danych SQL Język zapytań DQL — polecenie SELECT Język manipulowania danymi — DML Język definiowania danych — DDL Proces logowania do bazy Twoje dane w dobrej bazie to klucz do sukcesu!

Become a Python Data Analyst. Perform exploratory data analysis and gain insight into scientific computing using Python

Alvaro Fuentes

Python is one of the most common and popular languages preferred by leading data analysts and statisticians for working with massive datasets and complex data visualizations.Become a Python Data Analyst introduces Python’s most essential tools and libraries necessary to work with the data analysis process, right from preparing data to performing simple statistical analyses and creating meaningful data visualizations.In this book, we will cover Python libraries such as NumPy, pandas, matplotlib, seaborn, SciPy, and scikit-learn, and apply them in practical data analysis and statistics examples. As you make your way through the chapters, you will learn to efficiently use the Jupyter Notebook to operate and manipulate data using NumPy and the pandas library. In the concluding chapters, you will gain experience in building simple predictive models and carrying out statistical computation and analysis using rich Python tools and proven data analysis techniques.By the end of this book, you will have hands-on experience performing data analysis with Python.

Beginning Serverless Architectures with Microsoft Azure. Design scalable applications and microservices that effortlessly adapt to the requirements of your customers

Daniel Bass

Many businesses are rapidly adopting a microservices-first approach to development, driven by the availability of new commercial services like Azure Functions and AWS Lambda. In this book, we’ll show you how to quickly get up and running with your own serverless development on Microsoft Azure. We start by working through a single function, and work towards integration with other Azure services like App Insights and Cosmos DB to handle common user requirements like analytics and highly performant distributed storage. We finish up by providing you with the context you need to get started on a larger project of your own choosing, leaving you equipped with everything you need to migrate to a cloud-first serverless solution.

Big Data Analytics with Hadoop 3. Build highly effective analytics solutions to gain valuable insight into your big data

Sridhar Alla

Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples.Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases.By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly.

Big Data. Krótkie Wprowadzenie 30

Dawn E. Holmes

KRÓTKIE WPROWADZENIE - książki, które zmieniają sposób myślenia!   Big data pokazuje, jak postęp technologiczny spowodowany rozwojem Internetu i cyfrowego wszechświata wpłynął na radykalną transformację nauki o danych. Czym są duże zbiory danych i jak zmieniają świat? Jaki mają wpływ na nasze codzienne życie, a jaki na świat biznesu? W tej książce czytelnik znajdzie odpowiedzi na te pytania. * Interdyscyplinarna seria KRÓTKIE WPROWADZENIE piórem uznanych ekspertów skupionych wokół Uniwersytetu Oksfordzkiego przybliża aktualną wiedzę na temat współczesnego świata i pomaga go zrozumieć. W atrakcyjny sposób prezentuje najważniejsze zagadnienia XXI w. – od kultury, religii, historii przez nauki przyrodnicze po technikę. To publikacje popularnonaukowe, które w formule przystępnej, dalekiej od akademickiego wykładu, prezentują wybrane kwestie. Książki idealne zarówno jako wprowadzenie do nowych tematów, jak i uzupełnienie wiedzy o tym, co nas pasjonuje. Najnowsze fakty, analizy ekspertów, błyskotliwe interpretacje. Opiekę merytoryczną nad polską edycją serii sprawują naukowcy z Uniwersytetu Łódzkiego: prof. Krystyna Kujawińska Courtney, prof. Ewa Gajewska, prof. Aneta Pawłowska, prof. Jerzy Gajdka, prof. Piotr Stalmaszczyk.

Blockchain across Oracle. Understand the details and implications of the Blockchain for Oracle developers and customers

Robert van Molken

Blockchain across Oracle gives you the professional orientation to Blockchain that you need as an Oracle developer in today’s changing world. Written and prepared for you by Oracle Developer Champion Robert van Mölken, this book gets you up to speed with the details of the Blockchain - core concepts, how to implement Oracle’s Blockchain Cloud Service, industry implications for the Blockchain, and how the Blockchain will affect your Oracle customers.Robert van Mölken introduces you to the history and concepts of the Blockchain. You’ll really get to understand the Blockchain inside and out, as an Oracle developer or solution architect. You’ll understand the Blockchain flow, and how the hashes and chains create a new decentralised paradigm for you as an Oracle developer. You’ll gain insights into how the Blockchain affects Oracle developers and customers in this modern and disruptive era. You’ll see how the Blockchain concepts work in this new world where Assets, Transactions, Security, and Privacy, can all be sustained across a decentralized system for your customers.Then you'll find a detailed look at the cutting-edge Oracle middleware solutions. You’ll learn about Hyperledger Fabric, the opensource Blockchain framework used by Oracle as its core, and how to set up your own Oracle Blockchain Network. You’ll design and develop a smart contract, and learn how to run it on the Oracle Blockchain Cloud Service.The final part of the book looks at how the Blockchain will affect your customers across various industry sectors. By studying industry trends in the financial services sector, healthcare industry, and the transport industry, you’ll discover how the options and possibilities for you and your clients are being transformed by the Blockchain across Oracle. You’ll complete this professional orientation by looking at Blockchain trends and future directions.

Blockchain Development with Hyperledger. Build decentralized applications with Hyperledger Fabric and Composer

Salman A. Baset, Luc Desrosiers, Nitin Gaur, Petr Novotny, ...

Blockchain and Hyperledger are open source technologies that power the development of decentralized applications. This Learning Path is your helpful reference for exploring and building blockchain networks using Ethereum, Hyperledger Fabric, and Hyperledger Composer.Blockchain Development with Hyperledger will start off by giving you an overview of blockchain and demonstrating how you can set up an Ethereum development environment for developing, packaging, building, and testing campaign-decentralized applications. You'll then explore the de facto language Solidity, which you can use to develop decentralized applications in Ethereum. Following this, you'll be able to configure Hyperledger Fabric and use it to build private blockchain networks and applications that connect to them. Toward the later chapters, you'll learn how to design and launch a network, and even implement smart contracts in chain code. By the end of this Learning Path, you'll be able to build and deploy your own decentralized applications by addressing the key pain points encountered in the blockchain life cycle.This Learning Path includes content from the following Packt products:• Blockchain Quick Start Guide by Xun (Brian) Wu and Weimin Sun• Hands-On Blockchain with Hyperledger by Nitin Gaur et al.

Building Analytics Teams. Harnessing analytics and artificial intelligence for business improvement

John K. Thompson, Douglas B. Laney

In Building Analytics Teams, John K. Thompson, with his 30+ years of experience and expertise, illustrates the fundamental concepts of building and managing a high-performance analytics team, including what to do, who to hire, projects to undertake, and what to avoid in the journey of building an analytically sound team. The core processes in creating an effective analytics team and the importance of the business decision-making life cycle are explored to help achieve initial and sustainable success.The book demonstrates the various traits of a successful and high-performing analytics team and then delineates the path to achieve this with insights on the mindset, advanced analytics models, and predictions based on data analytics. It also emphasizes the significance of the macro and micro processes required to evolve in response to rapidly changing business needs.The book dives into the methods and practices of managing, developing, and leading an analytics team. Once you've brought the team up to speed, the book explains how to govern executive expectations and select winning projects.By the end of this book, you will have acquired the knowledge to create an effective business analytics team and develop a production environment that delivers ongoing operational improvements for your organization.

Building Blockchain Projects. Building decentralized Blockchain applications with Ethereum and Solidity

Narayan Prusty

Blockchain is a decentralized ledger that maintains a continuously growing list of data records that are secured from tampering and revision. Every user is allowed to connectto the network, send new transactions to it, verify transactions, and create new blocks,making it permission-less.This book will teach you what blockchain is, how it maintains data integrity, and how to create real-world blockchain projects using Ethereum. With interesting real-worldprojects, you will learn how to write smart contracts which run exactly as programmedwithout any chance of fraud, censorship, or third-party interference, and build end-to-eapplications for blockchain.You will learn about concepts such as cryptography in cryptocurrencies, ether security, mining, smart contracts, solidity, and more. You will also learn about web sockets, various API services for Ethereum, and much more.The blockchain is the main technical innovation of bitcoin, where it serves as the public ledger for bitcoin transactions.

Building ETL Pipelines with Python. Create and deploy enterprise-ready ETL pipelines by employing modern methods

Brij Kishore Pandey, Emily Ro Schoof

Modern extract, transform, and load (ETL) pipelines for data engineering have favored the Python language for its broad range of uses and a large assortment of tools, applications, and open source components. With its simplicity and extensive library support, Python has emerged as the undisputed choice for data processing.In this book, you’ll walk through the end-to-end process of ETL data pipeline development, starting with an introduction to the fundamentals of data pipelines and establishing a Python development environment to create pipelines. Once you've explored the ETL pipeline design principles and ET development process, you'll be equipped to design custom ETL pipelines. Next, you'll get to grips with the steps in the ETL process, which involves extracting valuable data; performing transformations, through cleaning, manipulation, and ensuring data integrity; and ultimately loading the processed data into storage systems. You’ll also review several ETL modules in Python, comparing their pros and cons when building data pipelines and leveraging cloud tools, such as AWS, to create scalable data pipelines. Lastly, you’ll learn about the concept of test-driven development for ETL pipelines to ensure safe deployments.By the end of this book, you’ll have worked on several hands-on examples to create high-performance ETL pipelines to develop robust, scalable, and resilient environments using Python.

Building Full Stack DeFi Applications. A practical guide to creating your own decentralized finance projects on blockchain

Samuel Zhou

Enter the world of Decentralized Finance (DeFi) with Building Full Stack DeFi Applications. Understand how this blockchain-based financial technology, designed to manage crypto assets, runs independently without centralized financial institutions like banks and brokerages, eliminating the fees that banks and other financial companies charge for using their services. This book will show you how DeFi solutions are built with smart contracts running on blockchains and how they allow users to gain and earn crypto assets based on the trust of the smart contracts.This book uncovers the inner workings of DeFi by guiding you through the mathematical foundations and teaching you how to build real-world DeFi products with Solidity and JavaScript. As you progress through the chapters, you’ll learn how to implement smart contracts of liquidity pools to trade cryptocurrencies and implement staking, including farming features that allow users to earn. You’ll also find out how to create asset pools that allow users to lend and borrow cryptocurrencies and generate interest. Additionally, you’ll discover how to use Web3 libraries to build the frontend of DeFi products.By the end of this book, you’ll will be well acquainted with popular tools, libraries, and design patterns for implementing a full-stack DeFi application with Web3 and Solidity.

Building Statistical Models in Python. Develop useful models for regression, classification, time series, and survival analysis

Huy Hoang Nguyen, Paul N Adams, Stuart J Miller

The ability to proficiently perform statistical modeling is a fundamental skill for data scientists and essential for businesses reliant on data insights. Building Statistical Models with Python is a comprehensive guide that will empower you to leverage mathematical and statistical principles in data assessment, understanding, and inference generation.This book not only equips you with skills to navigate the complexities of statistical modeling, but also provides practical guidance for immediate implementation through illustrative examples. Through emphasis on application and code examples, you’ll understand the concepts while gaining hands-on experience. With the help of Python and its essential libraries, you’ll explore key statistical models, including hypothesis testing, regression, time series analysis, classification, and more.By the end of this book, you’ll gain fluency in statistical modeling while harnessing the full potential of Python's rich ecosystem for data analysis.