ROS Robotics Projects. Make your robots see, sense, and interact with cool and engaging projects with Robotic Operating System

Lentin Joseph

Robot Operating System is one of the most widely used software frameworks for robotic research and for companies to model, simulate, and prototype robots. Applying your knowledge of ROS to actual robotics is much more difficult than people realize, but this title will give you what you need to create your own robotics in no time!This book is packed with over 14 ROS robotics projects that can be prototyped without requiring a lot of hardware. The book starts with an introduction of ROS and its installation procedure. After discussing the basics, you’ll be taken through great projects, such as building a self-driving car, an autonomous mobile robot, and image recognition using deep learning and ROS. You can find ROS robotics applications for beginner, intermediate, and expert levels inside!This book will be the perfect companion for a robotics enthusiast who really wants to do something big in the field.

Natural Language Processing and Computational Linguistics. A practical guide to text analysis with Python, Gensim, spaCy, and Keras

Bhargav Srinivasa-Desikan

Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data.This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy.You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning.This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis.

React Native Cookbook. Recipes for solving common React Native development problems - Second Edition

Daniel Ward

If you are a developer looking to create mobile applications with maximized code reusability and minimized cost, React Native is what you need. With this practical guide, you’ll be able to build attractive UIs, tackle common problems in mobile development, and achieve improved performance in mobile environments.This book starts by covering the common techniques for React Native customization and helps you set up your development platforms. Over the course of the book, you’ll work through a wide variety of recipes that help you create, style, and animate your apps with built-in React Native and custom third-party components. You’ll also develop real-world browser-based authentication, build a fully functional audio player, and integrate Google Maps in your apps. This book will help you explore different strategies for working with data, including leveraging the popular Redux library and optimizing your app’s dataflow. You’ll also learn how to write native device functionality for new and existing React Native projects and how app deployment works.By the end of this book, you'll be equipped with tips and tricks to write efficient code and have the skills to build full iOS and Android applications using React Native.

Apache Spark 2.x for Java Developers. Explore big data at scale using Apache Spark 2.x Java APIs

Sourav Gulati, Sumit Kumar

Apache Spark is the buzzword in the big data industry right now, especially with the increasing need for real-time streaming and data processing. While Spark is built on Scala, the Spark Java API exposes all the Spark features available in the Scala version for Java developers. This book will show you how you can implement various functionalities of the Apache Spark framework in Java, without stepping out of your comfort zone.The book starts with an introduction to the Apache Spark 2.x ecosystem, followed by explaining how to install and configure Spark, and refreshes the Java concepts that will be useful to you when consuming Apache Spark's APIs. You will explore RDD and its associated common Action and Transformation Java APIs, set up a production-like clustered environment, and work with Spark SQL. Moving on, you will perform near-real-time processing with Spark streaming, Machine Learning analytics with Spark MLlib, and graph processing with GraphX, all using various Java packages.By the end of the book, you will have a solid foundation in implementing components in the Spark framework in Java to build fast, real-time applications.

Distributed Computing in Java 9. Leverage the latest features of Java 9 for distributed computing

Raja Malleswara Rao Malleswara Rao Pattamsetti

Distributed computing is the concept with which a bigger computation process is accomplished by splitting it into multiple smaller logical activities and performed by diverse systems, resulting in maximized performance in lower infrastructure investment. This book will teach you how to improve the performance of traditional applications through the usage of parallelism and optimized resource utilization in Java 9.After a brief introduction to the fundamentals of distributed and parallel computing, the book moves on to explain different ways of communicating with remote systems/objects in a distributed architecture. You will learn about asynchronous messaging with enterprise integration and related patterns, and how to handle large amount of data using HPC and implement distributed computing for databases. Moving on, it explains how to deploy distributed applications on different cloud platforms and self-contained application development. You will also learn about big data technologies and understand how they contribute to distributed computing. The book concludes with the detailed coverage of testing, debugging, troubleshooting, and security aspects of distributed applications so the programs you build are robust, efficient, and secure.

Go Machine Learning Projects. Eight projects demonstrating end-to-end machine learning and predictive analytics applications in Go

Xuanyi Chew

Go is the perfect language for machine learning; it helps to clearly describe complex algorithms, and also helps developers to understand how to run efficient optimized code. This book will teach you how to implement machine learning in Go to make programs that are easy to deploy and code that is not only easy to understand and debug, but also to have its performance measured.The book begins by guiding you through setting up your machine learning environment with Go libraries and capabilities. You will then plunge into regression analysis of a real-life house pricing dataset and build a classification model in Go to classify emails as spam or ham. Using Gonum, Gorgonia, and STL, you will explore time series analysis along with decomposition and clean up your personal Twitter timeline by clustering tweets. In addition to this, you will learn how to recognize handwriting using neural networks and convolutional neural networks. Lastly, you'll learn how to choose the most appropriate machine learning algorithms to use for your projects with the help of a facial detection project.By the end of this book, you will have developed a solid machine learning mindset, a strong hold on the powerful Go toolkit, and a sound understanding of the practical implementations of machine learning algorithms in real-world projects.

Hands-On Dependency Injection in Go. Develop clean Go code that is easier to read, maintain, and test

Corey Scott

Hands-On Dependency Injection in Go takes you on a journey, teaching you about refactoring existing code to adopt dependency injection (DI) using various methods available in Go.Of the six methods introduced in this book, some are conventional, such as constructor or method injection, and some unconventional, such as just-in-time or config injection. Each method is explained in detail, focusing on their strengths and weaknesses, and is followed with a step-by-step example of how to apply it. With plenty of examples, you will learn how to leverage DI to transform code into something simple and flexible. You will also discover how to generate and leverage the dependency graph to spot and eliminate issues. Throughout the book, you will learn to leverage DI in combination with test stubs and mocks to test otherwise tricky or impossible scenarios.Hands-On Dependency Injection in Go takes a pragmatic approach and focuses heavily on the code, user experience, and how to achieve long-term benefits through incremental changes.By the end of this book, you will have produced clean code that’s easy to test.

Hands-On Ensemble Learning with R. A beginner's guide to combining the power of machine learning algorithms using ensemble techniques

Prabhanjan Narayanachar Tattar

Ensemble techniques are used for combining two or more similar or dissimilar machine learning algorithms to create a stronger model. Such a model delivers superior prediction power and can give your datasets a boost in accuracy.Hands-On Ensemble Learning with R begins with the important statistical resampling methods. You will then walk through the central trilogy of ensemble techniques – bagging, random forest, and boosting – then you'll learn how they can be used to provide greater accuracy on large datasets using popular R packages. You will learn how to combine model predictions using different machine learning algorithms to build ensemble models. In addition to this, you will explore how to improve the performance of your ensemble models.By the end of this book, you will have learned how machine learning algorithms can be combined to reduce common problems and build simple efficient ensemble models with the help of real-world examples.

Ethereum Projects for Beginners. Build blockchain-based cryptocurrencies, smart contracts, and DApps

Kenny Vaneetvelde

Ethereum enables the development of efficient, smart contracts that contain code. These smart contracts can interact with other smart contracts to make decisions, store data, and send Ether to others.Ethereum Projects for Beginners provides you with a clear introduction to creating cryptocurrencies, smart contracts, and decentralized applications. As you make your way through the book, you’ll get to grips with detailed step-by-step processes to build advanced Ethereum projects. Each project will teach you enough about Ethereum to be productive right away. You will learn how tokenization works, think in a decentralized way, and build blockchain-based distributed computing systems. Towards the end of the book, you will develop interesting Ethereum projects such as creating wallets and secure data sharing.By the end of this book, you will be able to tackle blockchain challenges by implementing end-to-end projects using the full power of the Ethereum blockchain.

Mastering Android Studio 3. Build Dynamic and Robust Android applications

Kyle Mew

Android Studio is an Integrated Development Environment (IDE) designed for developing Android apps. As with most development processes, Android keeps resources and logic nicely separated, and so this book covers the management of imagery and other resources, and the development and testing tools provided by the IDE.After introducing the software, the book moves straight into UI development using the sophisticated, WYSIWYG layout editor and XML code to design and test complex interfaces for a wide variety of screen configurations.With activity design covered, the book continues to guide the reader through application logic development, exploring the latest APIs provided by the SDK. Each topic will be demonstrated by working code samples that can be run on a device or emulator.One of Android Studio's greatest features is the large number of third-party plugins available for it, and throughout the book we will be exploring the most useful of these, along with samples and libraries that can be found on GitHub.The final module of the book deals with the final stages of development: building and distribution. The book concludes by taking the reader through the registration and publication processes required by Google. By the time you have finished the book, you will be able to build faster, smoother, and error-free Android applications, in less time and with fewer complications than you ever thought possible.

Big Data Analytics with Java. Data analysis, visualization & machine learning techniques

RAJAT MEHTA

This book covers case studies such as sentiment analysis on a tweet dataset, recommendations on a movielens dataset, customer segmentation on an ecommerce dataset, and graph analysis on actual flights dataset.This book is an end-to-end guide to implement analytics on big data withJava. Java is the de facto language for major big data environments, including Hadoop. This book will teach you how to perform analytics on big data with production-friendly Java. This book basically divided into twosections. The first part is an introduction that will help the readers get acquainted with big data environments, whereas the second part will contain a hardcore discussion on all the concepts in analyticson big data. It will take you from data analysis and data visualization to the core concepts and advantages of machine learning, real-life usage of regression and classification using Naïve Bayes, a deep discussion on the concepts of clustering,and a review of simple neural networkson big data using deepLearning4j or plain Java Spark code. This book is a must-have book for Java developers who want to start learning big data analytics and want to use it in the real world.

Python Machine Learning Cookbook. Over 100 recipes to progress from smart data analytics to deep learning using real-world datasets - Second Edition

Giuseppe Ciaburro, Prateek Joshi

This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks.With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning.By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples.

Blender for Video Production Quick Start Guide. Create high quality videos for YouTube and other social media platforms with Blender

Allan Brito

One of the critical components of any workflow related to video production is a reliable tool to create and edit media such as video and audio. In most cases, you will find video producers using software that can only cut and mount video in a traditional way. What if you could use a software that offers not only options to edit and cut video, but also create 3D content and animation? With Blender, you can make use of a fantastic set of tools to edit and cut video, and also produce 3D content that will enable you to take your productions to the next level.Do you want to take footage from a camera and cut or add sound and titles? This book will show you how Blender can do that for you! You will learn to add 3D virtual objects to the same footage that will help you to create a full 3D environment. Using some camera tricks, you can even turn Blender into a powerful 2.5D animation software to create compelling infographics to produce educational, marketing, and instructional videos. You will also learn how to work with motion tracking to mix live-action footage with virtual objects. You will then learn how to use the video editing capabilities of Blender and match 3D content to your project for YouTube or any other media.Toward the end of the book, you will export the project to YouTube using optimal settings for the best performance in the platform.

React 16 Essentials. A fast-paced, hands-on guide to designing and building scalable and maintainable web apps with React 16 - Second Edition

Artemij Fedosejev, Adam Boduch

React 16 Essentials, Second Edition, fully updated for React 16, takes you on a fast-paced journey through building your own maintainable React 16 applications. React experts Artemij Fedosejev and Adam Boduch give you all the essentials you need to know and start working with React 16, in this new edition of the best-selling React.js Essentials title. You'll find the latest React 16 code updates, assessment of React Fiber, new coverage of Redux, and how to work as a modern React developer.The authors offer you their current assessment of React Fiber, and you'll soon be exploring React 16 hands on, creating your own single and multiple user interface elements with React 16. You'll then see how to create stateless and stateful components and make them reactive. You'll also learn to interact between your components and lifecycle methods, and gauge how to effectively integrate your user interface components with other JavaScript libraries. Delve deep into the core elements of the Redux architecture and learn how to manage your application and data persistence. Then go the extra mile with the Jest test framework, and run multiple tests on your applications and find solutions to scale without complexity.Today React is used by Facebook, Instagram, Khan Academy, and Imperial College London, to name a few. Many new users recognize the benefits of React and adopt it in their own projects, forming a fast-growing community. The speed at which React has evolved promises a bright future for anyone who invests in learning it today. Let Artemij and Adam bring you a brand new look at React 16 and React Fiber, and move your web development into the future.

Tkinter GUI Programming by Example. Learn to create modern GUIs using Tkinter by building real-world projects in Python

David Love

Tkinter is a modular, cross-platform application development toolkit for Python. When developing GUI-rich applications, the most important choices are which programming language(s) and which GUI framework to use. Python and Tkinter prove to be a great combination. This book will get you familiar with Tkinter by having you create fun and interactive projects. These projects have varying degrees of complexity. We'll start with a simple project, where you'll learn the fundamentals of GUI programming and the basics of working with a Tkinter application. After getting the basics right, we'll move on to creating a project of slightly increased complexity, such as a highly customizable Python editor. In the next project, we'll crank up the complexity level to create an instant messaging app. Toward the end, we'll discuss various ways of packaging our applications so that they can be shared and installed on other machines without the user having to learn how to install and run Python programs.

ESP8266 Internet of Things Cookbook. Over 50 recipes to help you master the ESP8266's functionality

Marco Schwartz

The ESP8266 Wi-Fi Module is a self contained System on Chip (SOC) with an integrated TCP/IP protocol stack and can give any microcontroller access to your Wi-Fi network. It is capable of either hosting an application or offloading all Wi-Fi networking functions from another application processor.This book contains practical recipes that will help you master all ESP8266 functionalities. You will start by configuring and customizing the chip in line with your requirements. Then you will focus on core topics such as on-board processing, sensors, GPIOs, programming, networking, integration with external components, and so on. We will also teach you how to leverage Arduino using the ESP8266 and you'll learn about its libraries, file system, OTA updates, and so on. The book also provide recipes on web servers, testing, connecting with the cloud, and troubleshooting techniques. Programming aspects include MicroPython and how to leverage it to get started with the ESP8266. Towards the end, we will use these concepts and create an interesting project (IOT).By the end of the book, readers will be proficient enough to use the ESP8266 board efficiently.

Mastering Python Networking. Your one-stop solution to using Python for network automation, DevOps, and Test-Driven Development - Second Edition

Eric Chou

Networks in your infrastructure set the foundation for how your application can be deployed, maintained, and serviced. Python is the ideal language for network engineers to explore tools that were previously available to systems engineers and application developers. In this second edition of Mastering Python Networking, you’ll embark on a Python-based journey to transition from traditional network engineers to network developers ready for the next-generation of networks. This book begins by reviewing the basics of Python and teaches you how Python can interact with both legacy and API-enabled network devices. As you make your way through the chapters, you will then learn to leverage high-level Python packages and frameworks to perform network engineering tasks for automation, monitoring, management, and enhanced security. In the concluding chapters, you will use Jenkins for continuous network integration as well as testing tools to verify your network. By the end of this book, you will be able to perform all networking tasks with ease using Python.

Machine Learning with TensorFlow 1.x. Second generation machine learning with Google's brainchild - TensorFlow 1.x

Saif Ahmed, Quan Hua, Shams Ul Azeem

Google's TensorFlow is a game changer in the world of machine learning. It has made machine learning faster, simpler, and more accessible than ever before. This book will teach you how to easily get started with machine learning using the power of Python and TensorFlow 1.x. Firstly, you’ll cover the basic installation procedure and explore the capabilities of TensorFlow 1.x. This is followed by training and running the first classifier, and coverage of the unique features of the library including data ?ow graphs, training, and the visualization of performance with TensorBoard—all within an example-rich context using problems from multiple industries. You’ll be able to further explore text and image analysis, and be introduced to CNN models and their setup in TensorFlow 1.x. Next, you’ll implement a complete real-life production system from training to serving a deep learning model. As you advance you’ll learn about Amazon Web Services (AWS) and create a deep neural network to solve a video action recognition problem. Lastly, you’ll convert the Caffe model to TensorFlow and be introduced to the high-level TensorFlow library, TensorFlow-Slim.By the end of this book, you will be geared up to take on any challenges of implementing TensorFlow 1.x in your machine learning environment.

Java Data Science Cookbook. Explore the power of MLlib, DL4j, Weka, and more

Rushdi Shams

If you are looking to build data sciencemodels that are good for production,Java has come to the rescue. With the aidof strong libraries such as MLlib, Weka,DL4j, and more, you can efficientlyperform all the data science tasks youneed to.This unique book provides modernrecipes to solve your common andnot-so-common data science-relatedproblems. We start with recipes to helpyou obtain, clean, index, and search data.Then you will learn a variety of techniquesto analyze, learn from, and retrieveinformation from data. You will alsounderstand how to handle big data, learndeeply from data, and visualize data.Finally, you will work through uniquerecipes that solve your problems whiletaking data science to production, writingdistributed data science applications,and much more - things that will come inhandy at work.

Python for Finance. Apply powerful finance models and quantitative analysis with Python - Second Edition

Yuxing Yan

This book uses Python as its computational tool. Since Python is free, any school ororganization can download and use it. This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance.The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory,options and futures.This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM’s market risk,running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option.

Practical Industrial Internet of Things Security. A practitioner's guide to securing connected industries

Sravani Bhattacharjee

Securing connected industries and autonomous systems is of primary concern to the Industrial Internet of Things (IIoT) community. Unlike cybersecurity, cyber-physical security directly ties to system reliability as well as human and environmental safety.This hands-on guide begins by establishing the foundational concepts of IIoT security with the help of real-world case studies, threat models, and reference architectures. You’ll work with practical tools to design risk-based security controls for industrial use cases and gain practical knowledge of multi-layered defense techniques, including identity and access management (IAM), endpoint security, and communication infrastructure. You’ll also understand how to secure IIoT lifecycle processes, standardization, and governance. In the concluding chapters, you’ll explore the design and implementation of resilient connected systems with emerging technologies such as blockchain, artificial intelligence, and machine learning.By the end of this book, you’ll be equipped with the all the knowledge required to design industry-standard IoT systems confidently.

Learn to Create WordPress Themes by Building 5 Projects. Master the fundamentals of WordPress theme development and create attractive WordPress themes from scratch

Eduonix Learning Solutions

WordPress has emerged as a powerful, easy-to-use tool to design attractive, engaging websites. Themes play a big role in making WordPress as popular as it is today, and having an eye-catching, fully-functional theme could separate your website from the rest!This book will help you take your first steps in the WordPress theme development process, with 5 different projects centered around creating unique and responsive WordPress themes. Start with creating a simple WordPress theme using HTML5, CSS, and PHP. Then, you will move on to incorporate different APIs, widgets, and tools such as Bootstrap and jQuery to create more dynamic and highly-functional themes. Whether you want to create a photo gallery theme, a highly customizable e-commerce theme, or a theme designed to suit a particular business, this book will teach you everything you need to know.By the end of this highly interactive book, you will have the required mastery to develop WordPress themes from scratch.

Healthcare Analytics Made Simple. Techniques in healthcare computing using machine learning and Python

Vikas (Vik) Kumar, Shameer Khader

In recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists’ work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes.This book is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed.By the end of this book, you will understand how to use Python for healthcare data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data through real-world algorithms and code examples.

Hands-On Machine Learning with IBM Watson. Leverage IBM Watson to implement machine learning techniques and algorithms using Python

James D. Miller

IBM Cloud is a collection of cloud computing services for data analytics using machine learning and artificial intelligence (AI). This book is a complete guide to help you become well versed with machine learning on the IBM Cloud using Python. Hands-On Machine Learning with IBM Watson starts with supervised and unsupervised machine learning concepts, in addition to providing you with an overview of IBM Cloud and Watson Machine Learning. You'll gain insights into running various techniques, such as K-means clustering, K-nearest neighbor (KNN), and time series prediction in IBM Cloud with real-world examples. The book will then help you delve into creating a Spark pipeline in Watson Studio. You will also be guided through deep learning and neural network principles on the IBM Cloud using TensorFlow. With the help of NLP techniques, you can then brush up on building a chatbot. In later chapters, you will cover three powerful case studies, including the facial expression classification platform, the automated classification of lithofacies, and the multi-biometric identity authentication platform, helping you to become well versed with these methodologies.By the end of this book, you will be ready to build efficient machine learning solutions on the IBM Cloud and draw insights from the data at hand using real-world examples.