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Deep Learning with TensorFlow, 2nd Edition
Deep Learning with TensorFlow, 2nd Edition

Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks. This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow v1.7, combined with other open source Python libraries. Throughout the book, you'll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way. You'll come away with an in-depth knowledge of machine learning techniques and the ...
Introduction to Machine Learning with R
Introduction to Machine Learning with R

Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, you'll first start to learn with regression modelling and then move into more advanced topics such as neural networks and tree-based methods. Finally, you'll delve into the frontier of machine learning, using the caret package in R. Once you develop a familiarity with topics such as the difference between regression and classification models, you'll be able to solve an array of machine learning problems. Author Scott V. Burger provides several examples to help you build a working knowledge of machine learning. Explore machine learning models, algorithms, and data training; Understand machine learning algorithms for supervised and unsupervised cases; Examine statistical concepts for designing data for use in models; Dive into linear regres ...
The Data-Driven Project Manager
The Data-Driven Project Manager

Discover solutions to common obstacles faced by project managers. Written as a business novel, the book is highly interactive, allowing readers to participate and consider options at each stage of a project. The book is based on years of experience, both through the author's research projects as well as his teaching lectures at business schools. The book tells the story of Emily Reed and her colleagues who are in charge of the management of a new tennis stadium project. The CEO of the company, Jacob Mitchell, is planning to install a new data-driven project management methodology as a decision support tool for all upcoming projects. He challenges Emily and her team to start a journey in exploring project data to fight against unexpected project obstacles. Data-driven project management is known in the academic literature as "dynamic scheduling" or "integrated project management and control." It is a project management methodology to plan, monitor, and control projects in progress ...
Optimizing Data-to-Learning-to-Action
Optimizing Data-to-Learning-to-Action

Apply a powerful new approach and method that ensures continuous performance improvement for your business. You will learn how to determine and value the people, process, and technology-based solutions that will optimize your organization's data-to-learning-to-action processes. This book describes in detail how to holistically optimize the chain of activities that span from data to learning to decisions to actions, an imperative for achieving outstanding performance in today's business environment. Adapting and integrating insights from decision science, constraint theory, and process improvement, the book provides a method that is clear, effective, and can be applied to nearly every business function and sector. You will learn how to systematically work backwards from decisions to data, estimate the flow of value along the chain, and identify the inevitable value bottlenecks. And, importantly, you will learn techniques for quantifying the value that can be attained by successful ...
Programming Interviews Exposed, 4th Edition
Programming Interviews Exposed, 4th Edition

Programming Interviews Exposed is the programmer's ideal first choice for technical interview preparation. Updated to reflect changing techniques and trends, this new fourth edition provides insider guidance on the unique interview process that today's programmers face. Online coding contests are being used to screen candidate pools of thousands, take-home projects have become commonplace, and employers are even evaluating a candidate's public code repositories at GitHub - and with competition becoming increasingly fierce, programmers need to shape themselves into the ideal candidate well in advance of the interview. This book doesn't just give you a collection of questions and answers, it walks you through the process of coming up with the solution so you learn the skills and techniques to shine on whatever problems you're given. This edition combines a thoroughly revised basis in classic questions involving fundamental data structures and algorithms with problems and step-by-step ...
Analyzing Data with Power BI and Power Pivot for Excel
Analyzing Data with Power BI and Power Pivot for Excel

How can you use Excel and Power BI to gain real insights into your information? As you examine your data, how do you write a formula that provides the numbers you need? The answers to both of these questions lie with the data model. This book introduces the basic techniques for shaping data models in Excel and Power BI. It's meant for readers who are new to data modeling as well as for experienced data modelers looking for tips from the experts. If you want to use Power BI or Excel to analyze data, the many real-world examples in this book will help you look at your reports in a different way - like experienced data modelers do. As you'll soon see, with the right data model, the correct answer is always a simple one! Gain an understanding of the basics of data modeling, including tables, relationships, and keys; Familiarize yourself with star schemas, snowflakes, and common modeling techniques; Learn the importance of granularity; Discover how to use multiple fact tables, like sales ...
Cloud Analytics with Google Cloud Platform
Cloud Analytics with Google Cloud Platform

With the ongoing data explosion, more and more organizations all over the world are slowly migrating their infrastructure to the cloud. These cloud platforms also provide their distinct analytics services to help you get faster insights from your data. This book will give you an introduction to the concept of analytics on the cloud, and the different cloud services popularly used for processing and analyzing data. If you're planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations to be kept in mind, and choose the best tools and alternatives for analytics, based on your requirements. The chapters in this book will take you through the 70+ services available in Google Cloud Platform and their implementation for practical purposes. From ingestion to processing your data, this book contains best practices on building an end-to-end analytics pipeline on the cloud by leveraging popular concepts such as machin ...
VMware Cross-Cloud Architecture
VMware Cross-Cloud Architecture

Over the past two decades, VMware vSphere has been known as the most trusted and reliable virtualization platform. VMware Cross-Cloud Architecture shows you how to design and configure Cross Cloud Architecture by using VMware Cloud Foundation and vRealize Suite with various use cases across private, public, and hybrid Cloud. This book takes you through everything from a basic understanding of virtualization to advanced aspects of storage and network virtualization, clustering, automation, and management. This book will be your guide to designing all aspects of Cloud. We start with the challenges faced by a traditional data center, define problem statements for you, and then brief you on respective solutions. Moving on, all kinds of virtualization and Cloud offerings from AWS and IBM Soft Layer are introduced and discussed in detail. Then, you'll learn how to design IT infrastructures for new and existing applications with a combination of Cloud Foundation, vRealize Suite, and vSp ...
Expert C++ Programming
Expert C++ Programming

C++ has come a long way and has now been adopted in several contexts. Its key strengths are its software infrastructure and resource-constrained applications. The C++ 17 release will change the way developers write code, and this course will help you master your developing skills with C++. With real-world, practical examples explaining each concept, the course is divided into three modules where will begin by introducing you to the latest features in C++ 17. It encourages clean code practices in C++ in general and demonstrates the GUI app-development options in C++. You'll get tips on avoiding memory leaks using smart-pointers. In the next module, you'll see how multi-threaded programming can help you achieve concurrency in your applications. We start with a brief introduction to the fundamentals of multithreading and concurrency concepts. We then take an in-depth look at how these concepts work at the hardware-level as well as how both operating systems and frameworks use these low-l ...
Web Scraping with Python, 2nd Edition
Web Scraping with Python, 2nd Edition

If programming is magic then web scraping is surely a form of wizardry. By writing a simple automated program, you can query web servers, request data, and parse it to extract the information you need. The expanded edition of this practical book not only introduces you web scraping, but also serves as a comprehensive guide to scraping almost every type of data from the modern web. Part I focuses on web scraping mechanics: using Python to request information from a web server, performing basic handling of the server's response, and interacting with sites in an automated fashion. Part II explores a variety of more specific tools and applications to fit any web scraping scenario you're likely to encounter. Parse complicated HTML pages; Develop crawlers with the Scrapy framework; Learn methods to store data you scrape; Read and extract data from documents; Clean and normalize badly formatted data; Read and write natural languages; Crawl through forms and logins; Scrape JavaScript and ...
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