Data Science is an emerging field and all the domains are becoming more dependent on data. In this book "Beginner’s Guide to Data Science", the author gives an introduction about Data Science. The book also put forward the different real-life examples of data science, the phases involved, the skill set required, the different algorithms used and the challenges of data science. The author has also provided an idea about the future of the field. This book will definitely be a good start on the topic.

This book is the result of several decades of teaching experience in data structures and algorithms. It is self-contained but does assume some prior knowledge of data structures, and a grasp of basic programming and mathematics tools. Basic Concepts in Algorithms focuses on more advanced paradigms and methods combining basic programming constructs as building blocks and their usefulness in the derivation of algorithms. Its coverage includes the algorithms' design process and an analysis of their performance.

Nеvеr before has our dаtа ѕесurіtу and оur рrіvасу bееn mоrе important. With so muсh оf оur information nоw being stored реrmаnеntlу оnlіnе, the possibility оf hаvіng thіѕ datataken іѕ an еvеr-рrеѕеnt thrеаt. Thе nеwѕ cycles аrе dоmіnаtеd bу stories оf threats to іndіvіduаl security аnd to іntеrnаtіоnаllу rесоgnіѕеd соmраnіеѕ tоо.Orgаnіѕеd cyber сrіmе is fаѕt bесоmіng a рrоblеm thаt ѕесurіtу fіrmѕ are ѕtrugglіng to fіght bасk against. Sоmе оf thеѕе сrіmе groups аrе аlmоѕt lіkе ѕtаrt-uрѕ, еmрlоуіng experienced wеb developers tо hack іntо data frames and ѕtеаl information. Thіѕ is where the world of суbеr security соmеѕ into play.

DO YOU WANT TO LEARN MS EXCEL WITHOUT HAVING TO WASTE TIME WITH UNSUCCESSFUL TUTORIALS OR BORING MANUALS?

ARE YOU A BEGINNER AND WANT TO BECOME AN EXPERT IN MS EXCEL IN 30 MINUTES A DAY?

Get quick hands-on experience with Google Cloud. This cookbook provides a variety of self-contained recipes that show you how to use Google Cloud services for your enterprise application. Whether you're looking for practical ways to apply microservices, AI, analytics, security, or networking solutions, these recipes take you step-by-step through the process and provide discussions that explain how and why the recipes work. Ideal for system engineers and administrators, developers, network and database administrators, and data analysts, this cookbook helps you get started with Google Cloud regardless of your level of experience.

Fully updated for Android Studio 4.2, the goal of this book is to teach the skills necessary to develop Android based applications using the Kotlin programming language. Beginning with the basics, this book provides an outline of the steps necessary to set up an Android development and testing environment followed by an introduction to programming in Kotlin including data types, flow control, functions, lambdas, and object-oriented programming.

Fully updated for Android Studio 4.2, the goal of this book is to teach the skills necessary to develop Android-based applications using the Java programming language.

Beginning with the basics, this book provides an outline of the steps necessary to set up an Android development and testing environment.

The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice.

Working with unbounded and fast-moving data streams has historically been difficult. But with Kafka Streams and ksqlDB, building stream processing applications is easy and fun. This practical guide shows data engineers how to use these tools to build highly scalable stream processing applications for moving, enriching, and transforming large amounts of data in real time.
Mitch Seymour, data services engineer at Mailchimp, explains important stream processing concepts against a backdrop of several interesting business problems. You'll learn the strengths of both Kafka Streams and ksqlDB to help you choose the best tool for each unique stream processing project. Non-Java developers will find the ksqlDB path to be an especially gentle introduction to stream processing.

Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack.