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Scala Data Analysis Cookbook
Scala Data Analysis Cookbook

This book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits. Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you'll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming dat ...
Creating Data Stories with Tableau Public
Creating Data Stories with Tableau Public

Tableau Public is a very useful tool in anyone's data reporting toolbox that allows authors to add an interactive data element to any article. It allows investigative journalists and bloggers to tell a “data story”, allowing others to explore your data visualization. The relative ease of Tableau Public visualization creation allows data stories to be developed rapidly. It allows readers to explore data associations in multiple-sourced public data, and uses state-of-the-art dashboard and chart graphics to immerse the users in an interactive experience. This book offers investigative journalists, bloggers, and other data story tellers a rich discussion of visualization creation topics, features, and functions. This book allows data story tellers to quickly gain confidence in understanding and expanding their visualization-creation knowledge, and allows them to quickly create interesting, interactive data visualizations to bring a richness and vibrancy to complex articles. The b ...
Reinforcement Learning
Reinforcement Learning

Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You'll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process. Reinforcement Learning discusses algorithm implementations important for reinforcement learning, including Markov's Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI before looking at Open AI Gym. You'll then learn about Swarm Intelligence with Python in terms of reinforcement learning. The last part of the book starts with the TensorFlow environment and gives an outline of how reinforcement learning can be applied to TensorFlow. There's also coverage of Keras, a framework that can be used with reinforcement learning. Finally, you'll delve into Google's Deep Mind and see scenarios where rein ...
Identity and Data Security for Web Development
Identity and Data Security for Web Development

Developers, designers, engineers, and creators can no longer afford to pass responsibility for identity and data security onto others. Web developers who don't understand how to obscure data in transmission, for instance, can open security flaws on a site without realizing it. With this practical guide, you'll learn how and why everyone working on a system needs to ensure that users and data are protected. Authors Jonathan LeBlanc and Tim Messerschmidt provide a deep dive into the concepts, technology, and programming methodologies necessary to build a secure interface for data and identity - without compromising usability. You'll learn how to plug holes in existing systems, protect against viable attack vectors, and work in environments that sometimes are naturally insecure.Understand the state of web and application security today;Design security password encryption, and combat password attack vectors;Create digital fingerprints to identify users through ...
Machine Learning and Security
Machine Learning and Security

Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you'll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters; Quickly detect anomalies, including breaches, fraud, and impending system failure; Conduct malware analysis by extracting useful information from computer binaries; Uncover at ...
R for Data Science
R for Data Science

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. ...
Clojure for Data Science
Clojure for Data Science

The term “data science” has been widely used to define this new profession that is expected to interpret vast datasets and translate them to improved decision-making and performance. Clojure is a powerful language that combines the interactivity of a scripting language with the speed of a compiled language. Together with its rich ecosystem of native libraries and an extremely simple and consistent functional approach to data manipulation, which maps closely to mathematical formula, it is an ideal, practical, and flexible language to meet a data scientist's diverse needs. Taking you on a journey from simple summary statistics to sophisticated machine learning algorithms, this book shows how the Clojure programming language can be used to derive insights from data. Data scientists often forge a novel path, and you'll see how to make use of Clojure's Java interoperability capabilities to access libraries such as Mahout and Mllib for which Clojure wrappers don't yet exist. Even seas ...
Beginning Windows 8 Data Development
Beginning Windows 8 Data Development

This book introduces novice developers to a range of data access strategies for storing and retreiving data both locally and remotely. It provides you with a range of fully working data access solutions and the insight you need to know when, and how, to apply each of the techniques to best advantage. Focussing specifically on how the Windows 8 app developer can work with the Windows Runtime (often called Windows RT) framework this book provides careful analysis of the many options you have open to you, along with a comparision of their strengths and weaknesses under different conditions. With the days of a single database being the right choice for almost all development projects long gone. You will lean that the right choice for your app now depends on a variety of factors and getting it right will be critical to your customer's end user experience. ...
Python Data Analysis Cookbook
Python Data Analysis Cookbook

Data analysis is a rapidly evolving field and Python is a multi-paradigm programming language suitable for object-oriented application development and functional design patterns. As Python offers a range of tools and libraries for all purposes, it has slowly evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning. Python Data Analysis Cookbook focuses on reproducibility and creating production-ready systems. You will start with recipes that set the foundation for data analysis with libraries such as matplotlib, NumPy, and pandas. You will learn to create visualizations by choosing color maps and palettes then dive into statistical data analysis using distribution algorithms and correlations. You'll then help you find your way around different data and numerical problems, get to grips with Spark and HDFS, and then set up migration scripts for web mining. In this book, you will dive deeper into recipes on spectral an ...
Moving to Office 365
Moving to Office 365

This book takes a concentrated look at the very latest best practices for Office 365 migration, with a focus on the needs of senior managers, IT managers, and others involved in key decisions when moving their business to the cloud. Based on popular chapters in his first book, Office 365: Migrating and Managing Your Business in the Cloud (Apress Open, co-authored with Don Crawford), author Matt Katzer revises and expands on his original material to bring you the very latest guidance on planning methods, management best practices, personnel decisions and migration and maintenance costs, along with brand new material on some of the most important and cutting-edge considerations when moving your business to the cloud: securing company data, and driving social collaboration in the workplace. Cloud technology provides a tremendous opportunity for an organization to reduce IT costs, and to improve productivity with increased mobile access, simpler administration, better security, and e ...
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