Biznes IT
Mastering PostgreSQL 10. Expert techniques on PostgreSQL 10 development and administration
Hans-Jürgen Schönig
PostgreSQL is an open source database used for handling large datasets (big data) and as a JSON document database. This book highlights the newly introduced features in PostgreSQL 10, and shows you how you can build better PostgreSQL applications, and administer your PostgreSQL database more efficiently. We begin by explaining advanced database design concepts in PostgreSQL 10, along with indexing and query optimization. You will also see how to work with event triggers and perform concurrent transactions and table partitioning, along with exploring SQL and server tuning. We will walk you through implementing advanced administrative tasks such as server maintenance and monitoring, replication, recovery, high availability, and much more. You will understand common and not-so-common troubleshooting problems and how you can overcome them. By the end of this book, you will have an expert-level command of advanced database functionalities and will be able to implement advanced administrative tasks with PostgreSQL 10.
James D. Miller , Rui Miguel Forte
R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems.The book begins with a dedicated chapter on the language of models and the predictive modeling process. You will understand the learning curve and the process of tidying data. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real-world datasets. How do you train models that can handle really large datasets? This book will also show you just that. Finally, you will tackle the really important topic of deep learning by implementing applications on word embedding and recurrent neural networks.By the end of this book, you will have explored and tested the most popular modeling techniques in use on real- world datasets and mastered a diverse range of techniques in predictive analytics using R.
Alvaro Fuentes
Python is a programming language that provides a wide range of features that can be used in the field of data science. Mastering Predictive Analytics with scikit-learn and TensorFlow covers various implementations of ensemble methods, how they are used with real-world datasets, and how they improve prediction accuracy in classification and regression problems.This book starts with ensemble methods and their features. You will see that scikit-learn provides tools for choosing hyperparameters for models. As you make your way through the book, you will cover the nitty-gritty of predictive analytics and explore its features and characteristics. You will also be introduced to artificial neural networks and TensorFlow, and how it is used to create neural networks. In the final chapter, you will explore factors such as computational power, along with improvement methods and software enhancements for efficient predictive analytics.By the end of this book, you will be well-versed in using deep neural networks to solve common problems in big data analysis.
Russell Anderson-Williams, John J Sylvia IV
If you use Prezi in business and want to take your presentations to the next level, or if you want to become the office Prezi master, this book is for you.
Ankur Ankan
Probabilistic Graphical Models is a technique in machine learning that uses the concepts of graph theory to compactly represent and optimally predict values in our data problems. In real world problems, it's often difficult to select the appropriate graphical model as well as the appropriate inference algorithm, which can make a huge difference in computation time and accuracy. Thus, it is crucial to know the working details of these algorithms.This book starts with the basics of probability theory and graph theory, then goes on to discuss various models and inference algorithms. All the different types of models are discussed along with code examples to create and modify them, and also to run different inference algorithms on them. There is a complete chapter devoted to the most widely used networks Naive Bayes Model and Hidden Markov Models (HMMs). These models have been thoroughly discussed using real-world examples.
Edward Unger, Ryan Coyne
Do you want to start a business or turn a hobby into a profession, but feel like you're running out of time? Do you want to become a productivity powerhouse, effectively juggling personal and professional responsibilities? Does your team need help boosting efficiency? This comprehensive guide provides practical strategies and action plans to optimize your work and home life using ClickUp.Achieve project success by setting meaningful KPIs, creating team dashboards, generating real-time reports, and extending ClickUp with integrations. You’ll learn how to implement and optimize your workspace structure, project management, processes, workflows, automation, AI, and how to use ClickUp Brain as a knowledgebase. This book also helps you master ClickUp for home life by using it to manage personal tasks, plan vacations, collaborate on projects, maintain interactive inventory, and track household chores. Finally, you'll explore advanced features, goal setting, and personal approaches to maximize your leverage of ClickUp as your 'accomplishment system.Whether you're a seasoned user or just getting started, this ClickUp handbook provides best practices and highlights common mistakes for implementing and optimizing ClickUp to unlock its potential and achieve your goals.
Samir Madhavan
Data science is a relatively new knowledge domain which is used by various organizations to make data driven decisions. Data scientists have to wear various hats to work with data and to derive value from it. The Python programming language, beyond having conquered the scientific community in the last decade, is now an indispensable tool for the data science practitioner and a must-know tool for every aspiring data scientist. Using Python will offer you a fast, reliable, cross-platform, and mature environment for data analysis, machine learning, and algorithmic problem solving.This comprehensive guide helps you move beyond the hype and transcend the theory by providing you with a hands-on, advanced study of data science.Beginning with the essentials of Python in data science, you will learn to manage data and perform linear algebra in Python. You will move on to deriving inferences from the analysis by performing inferential statistics, and mining data to reveal hidden patterns and trends. You will use the matplot library to create high-end visualizations in Python and uncover the fundamentals of machine learning. Next, you will apply the linear regression technique and also learn to apply the logistic regression technique to your applications, before creating recommendation engines with various collaborative filtering algorithms and improving your predictions by applying the ensemble methods.Finally, you will perform K-means clustering, along with an analysis of unstructured data with different text mining techniques and leveraging the power of Python in big data analytics.
James Ma Weiming
If you are an undergraduate or graduate student, a beginner to algorithmic development and research, or a software developer in the financial industry who is interested in using Python for quantitative methods in finance, this is the book for you. It would be helpful to have a bit of familiarity with basic Python usage, but no prior experience is required.
ANDRIY LESYUK
Redmine is not only one of the popular open source project management applications but also one of the best project hosting and issue tracking solutions.This book is an update of our previous successful edition, Mastering Redmine. This book is a comprehensive guide that will give you a detailed practical understanding on how to effectively manage, monitor and administer complex projects using Redmine.You will get familiar with the concept of Issue Tracking and will get to know why and what makes Redmine one of the best issue trackers. Another main part of Redmine functionality, which is Managing projects shows why this is one of the best applications for project hosting. Furthermore, you will learn more about Redmine rich text formatting syntax, access control and workflow and time Tracking. Towards the end, you will unleash the power of custom fields and guides to show how to customize Redmine without breaking upgrade compatibility.By the end of the book, you will have a deep practical understanding on how to effectively monitor and manage large scale and complex projects using Redmine.
Mastering Salesforce Experience Cloud. Strategies for creating powerful customer interactions
Lillie Beiting, Rachel Rogers
Empowering your target audience to interact effortlessly with you and your product offerings is a critical aspect of business in the modern era. Users expect easy, professional digital experiences when engaging with organizations. However, creating engagement applications from scratch is challenging, and connecting user behavior with your organization’s data is even more complex. Enter Salesforce Experience Cloud sites, website portals built on the Salesforce data model that seamlessly connects your user data to your user experience. Mastering Salesforce Experience Cloud focuses on the human-centric nature of this product, beginning with a comprehensive guide on designing for your organization’s desired users and ensuring success for both internal teams and end users. After exploring the real-world applications of Experience Cloud and reviewing license models, this book provides a beginning-to-end guide to mastering the technical backend of this product, covering both out-of-the-box settings and customization techniques. By the end of this book, you’ll have gained a deep understanding of the Experience Cloud data model and customization options to create engaging, user-centric digital experiences that deliver value to your organization and stakeholders.
Paul Gerrard
If you want to learn how to quantitatively answer scientific questions for practical purposes using the powerful R language and the open source R tool ecosystem, this book is ideal for you. It is ideally suited for scientists who understand scientific concepts, know a little R, and want to be able to start applying R to be able to answer empirical scientific questions. Some R exposure is helpful, but not compulsory.
Mastering Spark for Data Science. Lightning fast and scalable data science solutions
Andrew Morgan, Antoine Amend, Matthew Hallett, David...
Data science seeks to transform the world using data, and this is typically achievedthrough disrupting and changing real processes in real industries. In order to operate at this level you need to build data science solutions of substance –solutions that solve real problems. Spark has emerged as the big data platform of choice for data scientists due to its speed, scalability, and easy-to-use APIs.This book deep dives into using Spark to deliver production-grade data sciencesolutions. This process is demonstrated by exploring the construction of a sophisticated global news analysis service that uses Spark to generate continuous geopolitical and current affairs insights.You will learn all about the core Spark APIs and take a comprehensive tour of advanced libraries, including Spark SQL, Spark Streaming, MLlib, and more.You will be introduced to advanced techniques and methods that will help you to construct commercial-grade data products. Focusing on a sequence of tutorials that deliver a working news intelligence service, you will learn about advanced Spark architectures, how to work with geographic data in Spark, and how to tune Spark algorithms so they scale linearly.
Marleen Meier, David Baldwin
Tableau is one of the leading business intelligence (BI) tools used to solve BI and analytics challenges. With this book, you will master Tableau's features and offerings in various paradigms of the BI domain. This book is also the second edition of the popular Mastering Tableau series, with new features, examples, and updated code. The book covers essential Tableau concepts and its advanced functionalities. Using Tableau Hyper and Tableau Prep, you’ll be able to handle and prepare data easily. You’ll gear up to perform complex joins, spatial joins, union, and data blending tasks using practical examples. Following this, you’ll learn how to perform data densification to make displaying granular data easier. Next, you’ll explore expert-level examples to help you with advanced calculations, mapping, and visual design using various Tableau extensions. With the help of examples, you’ll also learn about improving dashboard performance, connecting Tableau Server, and understanding data visualizations. In the final chapters, you’ll cover advanced use cases such as Self-Service Analytics, Time Series Analytics, and Geo-Spatial Analytics, and learn to connect Tableau to R, Python, and MATLAB. By the end of this book, you’ll have mastered the advanced offerings of Tableau and be able to tackle common and not-so-common challenges faced in the BI domain.
Armando Fandango, Ajit Jaokar
TensorFlow is the most popular numerical computation library built from the ground up for distributed, cloud, and mobile environments. TensorFlow represents the data as tensors and the computation as graphs.This book is a comprehensive guide that lets you explore the advanced features of TensorFlow 1.x. Gain insight into TensorFlow Core, Keras, TF Estimators, TFLearn, TF Slim, Pretty Tensor, and Sonnet. Leverage the power of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Throughout the book, you will obtain hands-on experience with varied datasets, such as MNIST, CIFAR-10, PTB, text8, and COCO-Images.You will learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF Clusters, deploy production models with TensorFlow Serving, and build and deploy TensorFlow models for mobile and embedded devices on Android and iOS platforms. You will see how to call TensorFlow and Keras API within the R statistical software, and learn the required techniques for debugging when the TensorFlow API-based code does not work as expected.The book helps you obtain in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems. By the end of this guide, you will have mastered the offerings of TensorFlow and Keras, and gained the skills you need to build smarter, faster, and efficient machine learning and deep learning systems.
Jeffrey Silver, Jason Mar-Tang, Michael Huckaby
Sales engineers often need to balance their technical expertise with the soft skills needed to close deals and build lasting client relationships. This book provides a framework for both senior engineers seeking professional growth and individuals just starting their sales engineering careers. This book draws from the authors’ extensive experience in this industry and as leaders in top high-tech companies, offering real-world insights and life lessons applicable to this specialized and in-demand industry. You’ll pick up the core disciplines a successful sales engineer should exemplify, along with mastering practical, day-to-day operational aspects. Within these chapters, you will learn the roles and responsibilities of a sales engineer, as well as adjacent roles within a sales team. You’ll also develop the skills needed to navigate complex sales cycles and exceed traditional expectations. This book covers various key aspects of sales engineering, including mastering communication techniques, navigating complex meetings, managing customer expectations, understanding legal matters, and handling administrative tasks. By the end of this book, you’ll have acquired advanced knowledge to excel as a world-class sales engineer and become a valuable member of your organization’s broader team.
Jeffrey Silver, Jason Mar-Tang, Michael Huckaby
Sales engineers often need to balance their technical expertise with the soft skills needed to close deals and build lasting client relationships. This book provides a framework for both senior engineers seeking professional growth and individuals just starting their sales engineering careers. This book draws from the authors’ extensive experience in this industry and as leaders in top high-tech companies, offering real-world insights and life lessons applicable to this specialized and in-demand industry. You’ll pick up the core disciplines a successful sales engineer should exemplify, along with mastering practical, day-to-day operational aspects. Within these chapters, you will learn the roles and responsibilities of a sales engineer, as well as adjacent roles within a sales team. You’ll also develop the skills needed to navigate complex sales cycles and exceed traditional expectations. This book covers various key aspects of sales engineering, including mastering communication techniques, navigating complex meetings, managing customer expectations, understanding legal matters, and handling administrative tasks. By the end of this book, you’ll have acquired advanced knowledge to excel as a world-class sales engineer and become a valuable member of your organization’s broader team.
Jeffrey Silver, Jason Mar-Tang, Michael Huckaby
Sales engineers often need to balance their technical expertise with the soft skills needed to close deals and build lasting client relationships. This book provides a framework for both senior engineers seeking professional growth and individuals just starting their sales engineering careers. This book draws from the authors’ extensive experience in this industry and as leaders in top high-tech companies, offering real-world insights and life lessons applicable to this specialized and in-demand industry. You’ll pick up the core disciplines a successful sales engineer should exemplify, along with mastering practical, day-to-day operational aspects. Within these chapters, you will learn the roles and responsibilities of a sales engineer, as well as adjacent roles within a sales team. You’ll also develop the skills needed to navigate complex sales cycles and exceed traditional expectations. This book covers various key aspects of sales engineering, including mastering communication techniques, navigating complex meetings, managing customer expectations, understanding legal matters, and handling administrative tasks. By the end of this book, you’ll have acquired advanced knowledge to excel as a world-class sales engineer and become a valuable member of your organization’s broader team.
Matematyka dyskretna dla praktyków. Algorytmy i uczenie maszynowe w Pythonie
Ryan T. White, Archana Tikayat Ray
Mimo że osiągnięcia matematyczne stały się podwalinami algorytmiki, wielu inżynierów nie w pełni rozumie reguły matematyki dyskretnej. Nawet jeśli nie stanowi to szczególnego problemu w codziennej pracy, w końcu okazuje się, że matematyka dyskretna jest niezbędna do osiągnięcia prawdziwej biegłości w operowaniu algorytmami i w pracy na danych. Co więcej, znajomość tej dziedziny bardzo ułatwia rozwiązywanie problemów z zakresu uczenia maszynowego. W ten sposób praktyczna biegłość w matematyce zauważalnie poprawia wyniki pracy inżynierów. Ta książka jest kompleksowym wprowadzeniem do matematyki dyskretnej, przydatnym dla każdego, kto chce pogłębić i ugruntować swoje umiejętności informatyczne. W zrozumiały sposób przedstawiono tu metody matematyki dyskretnej i ich zastosowanie w algorytmach i analizie danych, włączając w to techniki uczenia maszynowego. Zaprezentowano również zasady oceny złożoności obliczeniowej algorytmów i używania wyników tej oceny do zarządzania pracą procesora. Omówiono także sposoby przechowywania struktur grafowych, ich przeszukiwania i znajdywania ścieżek między wierzchołkami. Pokazano też, jak wykorzystać przedstawione informacje podczas posługiwania się bibliotekami Pythona, takimi jak scikit-learn i NumPy. W książce między innymi: terminologia i metody matematyki dyskretnej zastosowanie metod matematyki dyskretnej w algorytmach i analizie danych algebra Boole'a i kombinatoryka w podstawowych strukturach algorytmów rozwiązywanie problemów z dziedziny teorii grafów zadania związane z uczeniem maszynowym a matematyka dyskretna Matematyka dyskretna - poznaj, zrozum, zastosuj!