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Podcasts
Conversation as an interface is the best way for machines to interact with us using the universally accepted human tool that is language. Chatbots and voice user interfaces are two flavors of conversational UIs. Chatbots are real-time, data-driven answer engines that talk in natural language and are context-aware. Voice user interfaces are driven by voice and can understand and respond to users using speech. This book covers both types of conversational UIs by leveraging APIs from multiple platforms. We'll take a project-based approach to understand how these UIs are built and the best use cases for deploying them. We'll start by building a simple messaging bot from the Facebook Messenger API to understand the basics of bot building. Then we move on to creating a Task model that can perform complex tasks such as ordering and planning events with the newly-acquired-by-Google Dialogflow and Microsoft Bot framework. We then turn to voice-enabled UIs that are capable of interacting with users using speech with Amazon Alexa and Google Home. By the end of the book, you will have created your own line of chatbots and voice UIs for multiple leading platforms.
Ankit Jain, Armando Fandango, Amita Kapoor
TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits—simplicity, efficiency, and flexibility—of using TensorFlow in various real-world projects. With the help of this book, you’ll not only learn how to build advanced projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem.To start with, you’ll get to grips with using TensorFlow for machine learning projects; you’ll explore a wide range of projects using TensorForest and TensorBoard for detecting exoplanets, TensorFlow.js for sentiment analysis, and TensorFlow Lite for digit classification.As you make your way through the book, you’ll build projects in various real-world domains, incorporating natural language processing (NLP), the Gaussian process, autoencoders, recommender systems, and Bayesian neural networks, along with trending areas such as Generative Adversarial Networks (GANs), capsule networks, and reinforcement learning. You’ll learn how to use the TensorFlow on Spark API and GPU-accelerated computing with TensorFlow to detect objects, followed by how to train and develop a recurrent neural network (RNN) model to generate book scripts.By the end of this book, you’ll have gained the required expertise to build full-fledged machine learning projects at work.
With Wearable-Tech Projects with the Raspberry Pi Zero, you will begin with learning how to install the required software for your upcoming projects. You will also learn how to control electronic devices with the GPIOZero Python library. Next, you will be creating some stylish wearable-tech projects such as a motion-reactive LED cap and a Tweet-activated LED T-shirt. Toward the end of the book, you will be creating some useful health and fitness wearable-tech projects; these will help you monitor your heart rate, track your movements with GPS, and count your footsteps with your own pedometer.By the end of the book, you will have created a range of wearable-tech projects and learned enough about your Raspberry Pi Zero that you should be able to adapt these projects further or come up with your own creations!
Learning VMware NSX. Next-generation network administration skills revealed - Second Edition
VMware NSX is a platform for the software-defined data center. It allows complex networking topologies to be deployed programmatically in seconds. SDNs allow ease of deployment, management, and automation in deploying and maintaining new networks while reducing and in some cases completely eliminating the need to deploy traditional networks. The book allows you a thorough understanding of implementing Software defined networks using VMware’s NSX. You will come across the best practices for installing and configuring NSX to setup your environment. Then you will get a brief overview of the NSX Core Components NSX’s basic architecture. Once you are familiar with everything, you will get to know how to deploy various NSX features. Furthermore, you will understand how to manage and monitor NSX and its associated services and features. In addition to this, you will also explore the best practices for NSX deployments. By the end of the book, you will be able to deploy Vmware NSX in your own environment with ease. This book can come handy if you are preparing for VMware NSX certification.
Reactive programming is an effective way to build highly responsive applications with an easy-to-maintain code base. This book covers the essential functional reactive concepts that will help you build highly concurrent, event-driven, and asynchronous applications in a simpler and less error-prone way.C++ Reactive Programming begins with a discussion on how event processing was undertaken by different programming systems earlier. After a brisk introduction to modern C++ (C++17), you’ll be taken through language-level concurrency and the lock-free programming model to set the stage for our foray into the Functional Programming model. Following this, you’ll be introduced to RxCpp and its programming model. You’ll be able to gain deep insights into the RxCpp library, which facilitates reactive programming. You’ll learn how to deal with reactive programming using Qt/C++ (for the desktop) and C++ microservices for the Web.By the end of the book, you will be well versed with advanced reactive programming concepts in modern C++ (C++17).
This book will start with the fundamentals of C programming and programming topics, such data types, functions, decision making, program loops, pointers, and structures, with the help of an Arduino board. Then you will get acquainted with Arduino interactions with sensors, LEDs, and autonomous systems and setting up the Arduino environment. Moving on you will also learn how to work on the digital and analog I/O, establish serial communications with autonomous systems, and integrate with electronic devices. By the end of the book, you will be able to make basic projects such as LED cube and smart weather system that leverages C.
Mastering Arduino. A project-based approach to electronics, circuits, and programming
Mastering Arduino is an all-in-one guide to getting the most out of your Arduino. This practical, no-nonsense guide teaches you all of the electronics and programming skills that you need to create advanced Arduino projects. This book is packed full of real-world projects for you to practice on, bringing all of the knowledge in the book together and giving you the skills to build your own robot from the examples in this book. The final two chapters discuss wireless technologies and how they can be used in your projects. The book begins with the basics of electronics, making sure that you understand components, circuits, and prototyping before moving on. It then performs the same function for code, getting you into the Arduino IDE and showing you how to connect the Arduino to a computer and run simple projects on your Arduino.Once the basics are out of the way, the next 10 chapters of the book focus on small projects centered around particular components, such as LCD displays, stepper motors, or voice synthesizers. Each of these chapters will get you familiar with the technology involved, how to build with it, how to program it, and how it can be used in your own projects.
Prabhanjan Narayanachar Tattar
Statistical Analysis involves collecting and examining data to describe the nature of data that needs to be analyzed. It helps you explore the relation of data and build models to make better decisions.This book explores statistical concepts along with R and Python, which are well integrated from the word go. Almost every concept has an R code going with it which exemplifies the strength of R and applications. The R code and programs have been further strengthened with equivalent Python programs. Thus, you will first understand the data characteristics, descriptive statistics and the exploratory attitude, which will give you firm footing of data analysis. Statistical inference will complete the technical footing of statistical methods. Regression, linear, logistic modeling, and CART, builds the essential toolkit. This will help you complete complex problems in the real world.You will begin with a brief understanding of the nature of data and end with modern and advanced statistical models like CART. Every step is taken with DATA and R code, and further enhanced by Python.The data analysis journey begins with exploratory analysis, which is more than simple, descriptive, data summaries. You will then apply linear regression modeling, and end with logistic regression, CART, and spatial statistics.By the end of this book you will be able to apply your statistical learning in major domains at work or in your projects.