This book introduces you to the world of data science. It
reveals the proper way to do data science. It covers essential
statistical and programming techniques to help you understand
data science from a broad perspective. Not only that, but it
provides a theoretical, technical, and mathematical foundation for
problem-solving...
The sample chapter should give you a very good idea of the quality and style of our book. In particular, be sure you are comfortable with the level and with our GoLang coding style. This book focuses on giving solutions for complex problems in data structures and...
This book is simplified version to make you fully understand JavaScript. This book is simple enough to make you fully understand JavaScript and ES6without wasting your time and buggle your brain with complex theories or explanations. This book is fully practical in nature and simplified...
Make your Splunk certification easier with this exam study guide that covers the User, Power User, and Enterprise Admin certifications. This book is divided into three parts. The first part focuses on the Splunk User and Power User certifications starting with how to install Splunk, Splunk Processing Language (SPL), field...
Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate....
This chapter gives an overview of quantum solutions. You will
see how quantum computing can be applied in real life. The
problem and solutions are presented with the solution benefits.
The solution benefits are automation, cost reduction and profit
improvements, efficiency improvement, and defect reduction.
The solutions...
Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you...
The book introduces the latest methods and algorithms developed in machine and deep learning (hybrid symbolic-numeric computations, robust statistical techniques for clustering and eliminating data as well as convolutional neural networks) dealing not only with images and the use of computers, but also their applications to visualization tasks...
This first chapter is a primer on how virtualization is used to
create a software-defined data center (an SDDC) . One of the
central pillars of the software-defined data center is the use of
software defined networking (SDN). To better understand
NSX-T (VMware’s SDN solution), it is best to first understand
the...
