Daily Dose for 2017.10.15

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Smart Internet of Things Projects
Deploying Raspberry Pi in the Classroom
R for Everyone, Second Edition
Streaming Data
Spark in Action
Storm Applied

Books/Videos on Sale (or Free) Today

These deals are good for today only, so be sure to take advantage of the pricing before the offers expire.

Free Smart Internet of Things Projects

Smart Internet of Things Projects Free Packt eBook by Agus Kurniawan (valid through 10/15 at 19:00 EST). This book covers Internet of Things, Python, OpenCV, Raspberry Pi, Arduino, Bayesian, Fuzzy Logic, Microsoft Azure IoT.

Publisher’s Description

Internet of Things (IoT) is a groundbreaking technology that involves connecting numerous physical devices to the Internet and controlling them. Creating basic IoT projects is common, but imagine building smart IoT projects that can extract data from physical devices, thereby making decisions by themselves.

Our book overcomes the challenge of analyzing data from physical devices and accomplishes all that your imagination can dream up by teaching you how to build smart IoT projects. Basic statistics and various applied algorithms in data science and machine learning are introduced to accelerate your knowledge of how to integrate a decision system into a physical device.

This book contains IoT projects such as building a smart temperature controller, creating your own vision machine project, building an autonomous mobile robot car, controlling IoT projects through voice commands, building IoT applications utilizing cloud technology and data science, and many more. We will also leverage a small yet powerful IoT chip, Raspberry Pi with Arduino, in order to integrate a smart decision-making system in the IoT projects.

What You Will Learn

  • Implement data science in your IoT projects and build a smart temperature controller
  • Create a simple machine learning application and implement decision system concepts
  • Develop a vision machine using OpenCV
  • Build a robot car with manual and automatic control
  • Implement speech modules with your own voice commands for IoT projects
  • Connect IoT to a cloud-based server

About the Author

Agus Kurniawan is a lecturer, IT consultant, and an author. He has experience in various software and hardware development projects, delivering materials in training and workshops, and delivering technical writing for 17 years. He has been awarded the Microsoft Most Valuable Professional (MVP) award for 13 years in a row.

He is currently doing some research and teaching activities related to networking and security systems at the Faculty of Computer Science, University of Indonesia, and the Samsung R&D Institute, Indonesia. Currently, he’s pursuing a PhD in Computer Science in Germany.

$9.99 Deploying Raspberry Pi in the Classroom

Deploying Raspberry Pi in the Classroom $9.99 Apress eBook by Guy Hart-Davis. This book covers Raspberry Pi.

Publisher’s Description

  • Develop programming basics in an easy-to-learn format in Python, Java, C, and other languages.
  • Plan your Raspberry Pi network and choose the right hardware and software.
  • Increase your classroom’s capabilities for digital development and content delivery.

Learn how to deploy Raspberry Pi computers in a classroom or lab situation and how to navigate the hardware and software choices you face.

Deploying Raspberry Pi in the Classroom equips you with the skills and knowledge to plan and execute a deployment of Raspberry Pi computers in the classroom. Teachers and IT administrators at schools will see how to set up the hardware and software swiftly on your own or with the help of your students.

Step-by-step instructions and practical examples walk you through building your Raspberry Pi workstations and your network, managing the computers and the network, and troubleshooting any problems that arise. This book offers several points to involve your students through hands-on activities. These activities are designed to benefit your beginner and older or more able students alike.

Make Deploying Raspberry Pi in the Classroom a part of you instructional library today.

What you will learn

  • Put an easily-manageable computer on each desk for students to learn Internet use and essential office software skills
  • Image, configure, and plan a classroom deployment of Raspberry Pi computers
  • Manage your classroom Raspberry Pi computers and keeping them up and running smoothly and efficiently

Who this book is for

Primary audience would be teachers and IT administrators at schools or colleges. It will also appeal to administrators at social clubs or organizations that provide less formal tuition or simply provide Internet access.

About the Author

Guy Hart-Davis is the author of more than 100 computer books, including several books from Apress—among them Learn Office 2016 for Mac, Learn Excel 2016 for Mac, and Pro Office for iPad.

$19.99 R for Everyone, Second Edition

R for Everyone, Second Edition $19.99 InformIT eBook by Jared P. Lander. This book covers R 3.4.0, ggplot2, dplyr, purrr, Tidyverse, Caret, knitr, LaTeX, RMarkdown, Shiny, RStudio.

Publisher’s Description

Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals

Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone, Second Edition, is the solution.

Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks.

Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualization; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. After all this you’ll make your code reproducible with LaTeX, RMarkdown, and Shiny.

By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most.

Coverage includes

  • Explore R, RStudio, and R packages
  • Use R for math: variable types, vectors, calling functions, and more
  • Exploit data structures, including data.frames, matrices, and lists
  • Read many different types of data
  • Create attractive, intuitive statistical graphics
  • Write user-defined functions
  • Control program flow with if, ifelse, and complex checks
  • Improve program efficiency with group manipulations
  • Combine and reshape multiple datasets
  • Manipulate strings using R’s facilities and regular expressions
  • Create normal, binomial, and Poisson probability distributions
  • Build linear, generalized linear, and nonlinear models
  • Program basic statistics: mean, standard deviation, and t-tests
  • Train machine learning models
  • Assess the quality of models and variable selection
  • Prevent overfitting and perform variable selection, using the Elastic Net and Bayesian methods
  • Analyze univariate and multivariate time series data
  • Group data via K-means and hierarchical clustering
  • Prepare reports, slideshows, and web pages with knitr
  • Display interactive data with RMarkdown and htmlwidgets
  • Implement dashboards with Shiny
  • Build reusable R packages with devtools and Rcpp

About the Author

Jared P. Lander is the Chief Data Scientist of Lander Analytics, a New York-based data science firm that specializes in statistical consulting and training services; the organizer of the New York Open Statistical Programming Meetup—the world’s largest R meetup—and the New York R Conference; and an adjunct professor of statistics at Columbia University.

With an M.A. from Columbia University in statistics and a B.S. from Muhlenberg College in mathematics, he has experience in both academic research and industry. Very active in the data community, Jared is a frequent speaker at conferences, universities, and meetups around the world. His writings on statistics can be found at jaredlander.com and his work has been featured in publications such as Forbes and The Wall Street Journal.

50% off Streaming Data Understanding the real-time pipeline

Streaming Data 50% off Manning’s eBook by Andrew G. Psaltis. This book covers Streaming Data, Apache Spark, Apache Storm, Apache Flink, Apache Samza, Apache Kafka.

Publisher’s Description

Streaming Data introduces the concepts and requirements of streaming and real-time data systems. The book is an idea-rich tutorial that teaches you to think about how to efficiently interact with fast-flowing data.

About the technology

As humans, we’re constantly filtering and deciphering the information streaming toward us. In the same way, streaming data applications can accomplish amazing tasks like reading live location data to recommend nearby services, tracking faults with machinery in real time, and sending digital receipts before your customers leave the shop. Recent advances in streaming data technology and techniques make it possible for any developer to build these applications if they have the right mindset. This book will let you join them.

About the book

Streaming Data is an idea-rich tutorial that teaches you to think about efficiently interacting with fast-flowing data. Through relevant examples and illustrated use cases, you’ll explore designs for applications that read, analyze, share, and store streaming data. Along the way, you’ll discover the roles of key technologies like Spark, Storm, Kafka, Flink, RabbitMQ, and more. This book offers the perfect balance between big-picture thinking and implementation details.

What’s inside

  • The right way to collect real-time data
  • Architecting a streaming pipeline
  • Analyzing the data
  • Which technologies to use and when

About the reader

Written for developers familiar with relational database concepts. No experience with streaming or real-time applications required.

About the author

Andrew Psaltis is a software engineer focused on massively scalable real-time analytics.

50% off Spark in Action

Spark in Action 50% off Manning’s eBook by Petar Zecevic, Marko Bonaci. This book covers Apache Spark 2.0, Streaming Data.

Publisher’s Description

Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. Fully updated for Spark 2.0.

About the technology

Big data systems distribute datasets across clusters of machines, making it a challenge to efficiently query, stream, and interpret them. Spark can help. It is a processing system designed specifically for distributed data. It provides easy-to-use interfaces, along with the performance you need for production-quality analytics and machine learning. Spark 2 also adds improved programming APIs, better performance, and countless other upgrades.

About the book

Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. You’ll get comfortable with the Spark CLI as you work through a few introductory examples. Then, you’ll start programming Spark using its core APIs. Along the way, you’ll work with structured data using Spark SQL, process near-real-time streaming data, apply machine learning algorithms, and munge graph data using Spark GraphX. For a zero-effort startup, you can download the preconfigured virtual machine ready for you to try the book’s code.

What’s inside

  • Updated for Spark 2.0
  • Real-life case studies
  • Spark DevOps with Docker
  • Examples in Scala, and online in Java and Python

About the reader

Written for experienced programmers with some background in big data or machine learning.

About the authors

Petar Zecevic and Marko Bonaci are seasoned developers heavily involved in the Spark community.

50% off Storm Applied Strategies for real-time event processing

Storm Applied 50% off Manning’s eBook by Sean T. Allen, Matthew Jankowski, Peter Pathirana with foreword by Andrew Montalenti. This book covers Apache Storm, Big Data, Streaming Data, Trident.

Publisher’s Description

Storm Applied is a practical guide to using Apache Storm for the real-world tasks associated with processing and analyzing real-time data streams. This immediately useful book starts by building a solid foundation of Storm essentials so that you learn how to think about designing Storm solutions the right way from day one. But it quickly dives into real-world case studies that will bring the novice up to speed with productionizing Storm.

About the technology

It’s hard to make sense out of data when it’s coming at you fast. Like Hadoop, Storm processes large amounts of data but it does it reliably and in real time, guaranteeing that every message will be processed. Storm allows you to scale with your data as it grows, making it an excellent platform to solve your big data problems.

About the book

Storm Applied is an example-driven guide to processing and analyzing real-time data streams. This immediately useful book starts by teaching you how to design Storm solutions the right way. Then, it quickly dives into real-world case studies that show you how to scale a high-throughput stream processor, ensure smooth operation within a production cluster, and more. Along the way, you’ll learn to use Trident for stateful stream processing, along with other tools from the Storm ecosystem.

What’s inside

  • Mapping real problems to Storm components
  • Performance tuning and scaling
  • Practical troubleshooting and debugging
  • Exactly-once processing with Trident

About the reader

This book moves through the basics quickly. While prior experience with Storm is not assumed, some experience with big data and real-time systems is helpful.

About the authors

Sean Allen, Matthew Jankowski, and Peter Pathirana lead the development team for a high-volume, search-intensive commercial web application at TheLadders.

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