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Microsoft Excel 2019 Formulas and Functions
Microsoft Excel 2019 Formulas and Functions

Expert Paul McFedries helps you master key Excel 2019 and Office 365 tools for building more powerful spreadsheets. Use Excel 2019 and Office 365 core features to build spreadsheets that solve business problems and deliver reliable answers. Drawing on his unsurpassed experience, Paul McFedries helps you make the most of formulas and functions, including the latest improvements to arrays, formula error handling, and statistics. McFedries' step-by-step projects walk you through handling key tasks, from building timesheets to projecting cash flow and aging receivables. His practical examples and clear instructions demystify intermediate- to advanced-level formula construction, and help you leverage Excel's most useful functions in your everyday work. Becoming an Excel expert has never been easier! By reading this book, you will: Improve business analyses by adding intelligence and knowledge to your models; Replace cumbersome formulas with convenient predefined functions; Radically ...
Mastering VMware vSphere 6.7
Mastering VMware vSphere 6.7

Mastering VMware vSphere 6.7 is the fully updated edition of the bestselling guide to VMware's virtualization solution. With comprehensive coverage of this industry-leading toolset, this book acts as an informative guide and valuable reference. Step-by-step instruction walks you through installation, configuration, operation, security processes, and much more as you conquer the management and automation of your virtual environment. Written by certified VMware vExperts, this indispensable guide provides hands-on instruction and detailed conceptual explanations, anchored by practical applications and real-world examples. This book is the ultimate guide to vSphere, helping administrators master their virtual environment. Learn to: Install, configure, and manage the vCenter Server components; Leverage the Support Tools to provide maintenance and updates; Create and configure virtual networks, storage devices, and virtual machines; Implement the latest features to ensure compatibility an ...
JavaScript Data Structures and Algorithms
JavaScript Data Structures and Algorithms

Explore data structures and algorithm concepts and their relation to everyday JavaScript development. A basic understanding of these ideas is essential to any JavaScript developer wishing to analyze and build great software solutions. You'll discover how to implement data structures such as hash tables, linked lists, stacks, queues, trees, and graphs. You'll also learn how a URL shortener, such as bit.ly, is developed and what is happening to the data as a PDF is uploaded to a webpage. This book covers the practical applications of data structures and algorithms to encryption, searching, sorting, and pattern matching. It is crucial for JavaScript developers to understand how data structures work and how to design algorithms. This book and the accompanying code provide that essential foundation for doing so. With JavaScript Data Structures and Algorithms you can start developing your knowledge and applying it to your JavaScript projects today. Review core data structure funda ...
MATLAB Machine Learning Recipes, 2nd Edition
MATLAB Machine Learning Recipes, 2nd Edition

Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem. All code in MATLAB Machine Learning Recipes: A Problem-Solution Approach is executable. The toolbox that the code uses provides a complete set of functions needed to implement all aspects of machine learning. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow the reader to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more. How to write code for machine learning, adaptive control and estimation using MATLAB; How these three areas complement each other; How these three areas are needed for robust machine learning applications; How to use MATLAB graphics and visualization tools for machine learning; How to code real world examples in MATLAB for major applications of ...
Scaling Your Startup
Scaling Your Startup

Know how your company can accelerate growth by not only tapping into new growth vectors, but also by adapting its organization, culture, and processes. To oversee growth from an idea to a company with billions in revenue, CEOs must reinvent many aspects of their company in anticipation of it reaching ever-higher revenues. Author Peter Cohan takes you through the four stages of scaling: winning the first customers, building a scalable business model, sprinting to liquidity, and running the marathon. Discover how founders keep their CEO positions by managing the organizational change needed to reach the next stage of scaling; Read case studies that illustrate how CEOs craft growth strategies, raise capital, create culture, build their organizations, set goals, and manage processes to achieve them; Discover principles of successful scaling through comparisons of successful and less successful companies; Use the Scaling Quotient to assess your startup's readiness to grow; Follow a ro ...
Deployment of Microsoft Azure Cloud Solutions
Deployment of Microsoft Azure Cloud Solutions

Microsoft Azure has numerous effective solutions that shape the future of any business. Over the years, Azure cloud services have grown quickly, and the number of organizations adopting Azure for their cloud services is also gradually increasing. Leading industry giants are finding that Azure fulfills their extensive cloud requirements. Deployment of Microsoft Azure Cloud Solutions starts with an extensive introduction to all the categories of designs available with Azure. These design patterns focus on different aspects of the cloud such as high availability, data management, and so on. You will learn various aspects such as building your cloud structure and architecture. You will also have a brief understanding of the different types of services provided by Azure, such as Azure functions and Azure Analytics, which can prove beneficial for an organization. You will learn each and every aspect and function required to develop an Azure cloud based on your organizational requiremen ...
Tableau 10 Complete Reference
Tableau 10 Complete Reference

Graphical presentation of data enables us to easily understand complex data sets. Tableau 10 Complete Reference provides easy-to-follow recipes with several use cases and real-world business scenarios to get you up and running with Tableau 10. This Learning Path begins with the history of data visualization and its importance in today's businesses. You'll also be introduced to Tableau - how to connect, clean, and analyze data in this visual analytics software. Then, you'll learn how to apply what you've learned by creating some simple calculations in Tableau and using Table Calculations to help drive greater analysis from your data. Next, you'll explore different advanced chart types in Tableau. These chart types require you to have some understanding of the Tableau interface and understand basic calculations. You'll study in detail all dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also cov ...
Deep Learning with PyTorch Quick Start Guide
Deep Learning with PyTorch Quick Start Guide

PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power. This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders. You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text. By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease. ...
Learn Type-Driven Development
Learn Type-Driven Development

Type-driven development is an approach that uses a static type system to achieve results including safety and efficiency. Types are used to express relationships and other assumptions directly in the code, and these assumptions are enforced by the compiler before the code is run. Learn Type-Driven Development covers how to use these type systems to check the logical consistency of your code. This book begins with the basic idea behind type-driven development. You'll learn about values (or terms) and how they contrast with types. As you progress through the chapters, you'll cover how to combine types and values inside modules and build structured types out of simpler ones. You'll then understand how to express choices or alternatives directly in the type system using variants, polymorphic variants, and generalized algebraic data types. You'll also get to grips with sum types, build sophisticated data types from generics, and explore functions that express change in the types of value ...
Bayesian Analysis with Python, 2nd Edition
Bayesian Analysis with Python, 2nd Edition

The 2nd edition of Bayesian Analysis with Python is an introduction to the main concepts of applied Bayesian inference and its practical implementation in Python using PyMC3, a state-of-the-art probabilistic programming library, and ArviZ, a new library for exploratory analysis of Bayesian models. The main concepts of Bayesian statistics are covered using a practical and computational approach. Synthetic and real data sets are used to introduce several types of models, such as generalized linear models for regression and classification, mixture models, hierarchical models, and Gaussian processes, among others. By the end of the book, you will have a working knowledge of probabilistic modeling and you will be able to design and implement Bayesian models for your own data science problems. After reading the book you will be better prepared to delve into more advanced material or specialized statistical modeling if you need to. ...
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