Biznes IT
Damien Bruyndonckx
Adobe Captivate is the industry-leading solution for authoring E-learning content. With adobe Captivate one can capture the on-screen action, enhance e-Learning projects, insert SCORM and AICC-compliant quizzes and then, publish your work in various formats for easy deployment on virtually any desktop and mobile device. Mastering Adobe Captivate 6 is a comprehensive guide to creating SCORM-compliant demonstrations, simulations and quizzes with Adobe Captivate. The sample projects demonstrate each and every feature of Adobe Captivate giving you the expertise you need to create and deploy your own professionalquality e-learning courses. Mastering Adobe Captivate 6 will guide you through the creation of three e-learning projects including a demonstration, a simulation and a SCORM-compliant quiz. The first part of the book will drive you through the main three steps of the Captivate production process. In the first step, we will use the powerful capture engine of Captivate to generate the needed slides and screenshots. In the second step, we will enhance our slides and screenshots using the objects provided by Captivate. These objects include animations, interactions, videos and more. In the third step, we will make our project available to the outside world by publishing it in various formats including Adobe Flash PDF, video, and even HTML 5. The second part of the book will focus on the advanced tools of Captivate. These tools include the questions slides that make up a quiz, SCORM and AICC compliance, localization of your e-Learning content and widgets among others. In the last chapter, you we will unleash the true power of Captivate by using the variables and the advanced actions to create a unique e-Learning experience.
Wajahat Karim, Siddharth Shekar
Game engines such as Unity are the power-tools behind the games we know and love. Unity is one of the most widely-used and best loved packages for game development and is used by everyone, from hobbyists to large studios, to create games and interactive experiences for the Web, desktop, mobile, and console. With Unity's intuitive, easy-to-learn toolset and this book, it's never been easier to become a game developer.You will begin with the basic concepts of Android game development, a brief history of Android games, the building blocks of Android games in Unity 5, and the basic flow of games. You will configure an empty project for the Jetpack Joyride Clone Game, add an environment and characters, and control them. Next you will walk through topics such as particle systems, camera management, prefabs, animations, triggers, colliders, and basic GUI systems. You will then cover the basic setup for 3D action fighting games, importing models, textures and controlling them with a virtual on-screen joystick. Later you will set up Scene for 3D Configuration, create basic gameplays, and manage input controls. Next you will learn to create the interface for the main menu, gameplay, game over, achievements, and high score screens. Finally you will polish your game with stats, sounds, and Social Networking, followed by testing the game on Android devices and then publishing it on Google Play, Amazon, and OUYA Stores.
Romeo Kienzler
Apache Spark is an in-memory, cluster-based Big Data processing system that provides a wide range of functionalities such as graph processing, machine learning, stream processing, and more. This book will take your knowledge of Apache Spark to the next level by teaching you how to expand Spark’s functionality and build your data flows and machine/deep learning programs on top of the platform.The book starts with a quick overview of the Apache Spark ecosystem, and introduces you to the new features and capabilities in Apache Spark 2.x. You will then work with the different modules in Apache Spark such as interactive querying with Spark SQL, using DataFrames and DataSets effectively, streaming analytics with Spark Streaming, and performing machine learning and deep learning on Spark using MLlib and external tools such as H20 and Deeplearning4j. The book also contains chapters on efficient graph processing, memory management and using Apache Spark on the cloud.By the end of this book, you will have all the necessary information to master Apache Spark, and use it efficiently for Big Data processing and analytics.
Mastering Apache Storm. Real-time big data streaming using Kafka, Hbase and Redis
Ankit Jain
Apache Storm is a real-time Big Data processing framework that processes large amounts of data reliably, guaranteeing that every message will be processed. Storm allows you to scale your data as it grows, making it an excellent platform to solve your big data problems. This extensive guide will help you understand right from the basics to the advanced topics of Storm.The book begins with a detailed introduction to real-time processing and where Storm fits in to solve these problems. You’ll get an understanding of deploying Storm on clusters by writing a basic Storm Hello World example. Next we’ll introduce you to Trident and you’ll get a clear understanding of how you can develop and deploy a trident topology. We cover topics such as monitoring, Storm Parallelism, scheduler and log processing, in a very easy to understand manner. You will also learn how to integrate Storm with other well-known Big Data technologies such as HBase, Redis, Kafka, and Hadoop to realize the full potential of Storm.With real-world examples and clear explanations, this book will ensure you will have a thorough mastery of Apache Storm. You will be able to use this knowledge to develop efficient, distributed real-time applications to cater to your business needs.
Paul Battisson
Applications built on the Salesforce platform are now a key part of many organizations' IT systems, with more complex and integrated solutions being delivered every day. As a Salesforce developer working with Apex, it is important to understand the range and variety of tools at your disposal, how and when to use them, and what the best practices are.This revised second edition includes a complete restructuring and five new chapters filled with detailed content on the latest Salesforce innovations including integrating with DataWeave in Apex, and utilizing Flow and Apex together to build scalable applications with Administrators.This Salesforce book starts with a discussion around common mistakes, debugging, exception handling, and testing. The second section focuses on the different asynchronous Apex programming options to help you build more scalable applications, before the third section focuses on integrations, including working with platform events and developing custom Apex REST web services. Finally, the book finishes with a section dedicated to profiling and improving the performance of your Apex including architecture. With code examples used to facilitate discussion throughout, by the end of the book you will be able to develop robust and scalable applications in Apex with confidence.
Mastering Arduino. A project-based approach to electronics, circuits, and programming
Jon Hoffman
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.
Christoph Körner, Marcel Alsdorf
Azure Machine Learning is a cloud service for accelerating and managing the machine learning (ML) project life cycle that ML professionals, data scientists, and engineers can use in their day-to-day workflows. This book covers the end-to-end ML process using Microsoft Azure Machine Learning, including data preparation, performing and logging ML training runs, designing training and deployment pipelines, and managing these pipelines via MLOps.The first section shows you how to set up an Azure Machine Learning workspace; ingest and version datasets; as well as preprocess, label, and enrich these datasets for training. In the next two sections, you'll discover how to enrich and train ML models for embedding, classification, and regression. You'll explore advanced NLP techniques, traditional ML models such as boosted trees, modern deep neural networks, recommendation systems, reinforcement learning, and complex distributed ML training techniques - all using Azure Machine Learning.The last section will teach you how to deploy the trained models as a batch pipeline or real-time scoring service using Docker, Azure Machine Learning clusters, Azure Kubernetes Services, and alternative deployment targets.By the end of this book, you’ll be able to combine all the steps you’ve learned by building an MLOps pipeline.
Christoph Körner, Kaijisse Waaijer
The increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models. This book will help you improve your knowledge of building ML models using Azure and end-to-end ML pipelines on the cloud.The book starts with an overview of an end-to-end ML project and a guide on how to choose the right Azure service for different ML tasks. It then focuses on Azure Machine Learning and takes you through the process of data experimentation, data preparation, and feature engineering using Azure Machine Learning and Python. You'll learn advanced feature extraction techniques using natural language processing (NLP), classical ML techniques, and the secrets of both a great recommendation engine and a performant computer vision model using deep learning methods. You'll also explore how to train, optimize, and tune models using Azure Automated Machine Learning and HyperDrive, and perform distributed training on Azure. Then, you'll learn different deployment and monitoring techniques using Azure Kubernetes Services with Azure Machine Learning, along with the basics of MLOps—DevOps for ML to automate your ML process as CI/CD pipeline.By the end of this book, you'll have mastered Azure Machine Learning and be able to confidently design, build and operate scalable ML pipelines in Azure.