Mastering Adobe Captivate 6. Take your e-learning content to the next level with this fantastic guide to mastering Adobe Captivate. You\'ll learn by completing three sample projects that cover everything. If you can use Windows or Mac you can do this course

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.

Machine Learning for Data Mining. Improve your data mining capabilities with advanced predictive modeling

Jesus Salcedo

Machine learning (ML) combined with data mining can give you amazing results in your data mining work by empowering you with several ways to look at data. This book will help you improve your data mining techniques by using smart modeling techniques.This book will teach you how to implement ML algorithms and techniques in your data mining work. It will enable you to pair the best algorithms with the right tools and processes. You will learn how to identify patterns and make predictions with minimal human intervention. You will build different types of ML models, such as the neural network, the Support Vector Machines (SVMs), and the Decision tree. You will see how all of these models works and what kind of data in the dataset they are suited for. You will learn how to combine the results of different models in order to improve accuracy. Topics such as removing noise and handling errors will give you an added edge in model building and optimization.By the end of this book, you will be able to build predictive models and extract information of interest from the dataset

Mastering JavaScript Functional Programming. Write clean, robust, and maintainable web and server code using functional JavaScript and TypeScript - Third Edition

Federico Kereki

Functional programming is a programming paradigm that uses functions for developing software. This book is filled with examples that enable you to leverage the latest JavaScript and TypeScript versions to produce modern and clean code, as well as teach you to how apply functional programming techniques to develop more efficient algorithms, write more concise code, and simplify unit testing.This book provides comprehensive coverage of the major topics in functional programming to produce shorter, clearer, and testable programs. You’ll begin by getting to grips with writing and testing pure functions, reducing side effects, as well as other key features to make your applications functional in nature. The book specifically explores techniques to simplify coding, apply recursion, perform high-level coding, learn ways to achieve immutability, implement design patterns, and work with data types.By the end of this book, you’ll have developed the practical programming skills needed to confidently enhance your applications by adding functional programming to wherever it’s most suitable.

BackTrack 5 Wireless Penetration Testing Beginner's Guide. Master bleeding edge wireless testing techniques with BackTrack 5

Vivek Ramachandran

Wireless has become ubiquitous in today’s world. The mobility and flexibility provided by it makes our lives more comfortable and productive. But this comes at a cost – Wireless technologies are inherently insecure and can be easily broken. BackTrack is a penetration testing and security auditing distribution that comes with a myriad of wireless networking tools used to simulate network attacks and detect security loopholes. Backtrack 5 Wireless Penetration Testing Beginner’s Guide will take you through the journey of becoming a Wireless hacker. You will learn various wireless testing methodologies taught using live examples, which you will implement throughout this book. The engaging practical sessions very gradually grow in complexity giving you enough time to ramp up before you get to advanced wireless attacks.This book will take you through the basic concepts in Wireless and creating a lab environment for your experiments to the business of different lab sessions in wireless security basics, slowly turn on the heat and move to more complicated scenarios, and finally end your journey by conducting bleeding edge wireless attacks in your lab.There are many interesting and new things that you will learn in this book – War Driving, WLAN packet sniffing, Network Scanning, Circumventing hidden SSIDs and MAC filters, bypassing Shared Authentication, Cracking WEP and WPA/WPA2 encryption, Access Point MAC spoofing, Rogue Devices, Evil Twins, Denial of Service attacks, Viral SSIDs, Honeypot and Hotspot attacks, Caffe Latte WEP Attack, Man-in-the-Middle attacks, Evading Wireless Intrusion Prevention systems and a bunch of other cutting edge wireless attacks.If you were ever curious about what wireless security and hacking was all about, then this book will get you started by providing you with the knowledge and practical know-how to become a wireless hacker.

Business Process Driven SOA using BPMN and BPEL. BPMN and BPEL - Go from Business Process Modeling to Orchestration and Service Oriented Architecture with this book and

Matjaz B. Juric, Kapil Pant, Matjaz B Juric

Time Series Analysis with Python Cookbook. Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation

Tarek A. Atwan

Time series data is everywhere, available at a high frequency and volume. It is complex and can contain noise, irregularities, and multiple patterns, making it crucial to be well-versed with the techniques covered in this book for data preparation, analysis, and forecasting.This book covers practical techniques for working with time series data, starting with ingesting time series data from various sources and formats, whether in private cloud storage, relational databases, non-relational databases, or specialized time series databases such as InfluxDB. Next, you’ll learn strategies for handling missing data, dealing with time zones and custom business days, and detecting anomalies using intuitive statistical methods, followed by more advanced unsupervised ML models. The book will also explore forecasting using classical statistical models such as Holt-Winters, SARIMA, and VAR. The recipes will present practical techniques for handling non-stationary data, using power transforms, ACF and PACF plots, and decomposing time series data with multiple seasonal patterns. Later, you’ll work with ML and DL models using TensorFlow and PyTorch.Finally, you’ll learn how to evaluate, compare, optimize models, and more using the recipes covered in the book.

Scalable Data Streaming with Amazon Kinesis. Design and secure highly available, cost-effective data streaming applications with Amazon Kinesis

Tarik Makota, Brian Maguire, Danny Gagne, Rajeev Chakrabarti

Amazon Kinesis is a collection of secure, serverless, durable, and highly available purpose-built data streaming services. This data streaming service provides APIs and client SDKs that enable you to produce and consume data at scale.Scalable Data Streaming with Amazon Kinesis begins with a quick overview of the core concepts of data streams, along with the essentials of the AWS Kinesis landscape. You'll then explore the requirements of the use case shown through the book to help you get started and cover the key pain points encountered in the data stream life cycle. As you advance, you'll get to grips with the architectural components of Kinesis, understand how they are configured to build data pipelines, and delve into the applications that connect to them for consumption and processing. You'll also build a Kinesis data pipeline from scratch and learn how to implement and apply practical solutions. Moving on, you'll learn how to configure Kinesis on a cloud platform. Finally, you’ll learn how other AWS services can be integrated into Kinesis. These services include Redshift, Dynamo Database, AWS S3, Elastic Search, and third-party applications such as Splunk.By the end of this AWS book, you’ll be able to build and deploy your own Kinesis data pipelines with Kinesis Data Streams (KDS), Kinesis Data Firehose (KFH), Kinesis Video Streams (KVS), and Kinesis Data Analytics (KDA).

Hands-On Deep Learning Algorithms with Python. Master deep learning algorithms with extensive math by implementing them using TensorFlow

Sudharsan Ravichandiran

Deep learning is one of the most popular domains in the AI space that allows you to develop multi-layered models of varying complexities. This book introduces you to popular deep learning algorithms—from basic to advanced—and shows you how to implement them from scratch using TensorFlow. Throughout the book, you will gain insights into each algorithm, the mathematical principles involved, and how to implement it in the best possible manner. The book starts by explaining how you can build your own neural networks, followed by introducing you to TensorFlow, the powerful Python-based library for machine learning and deep learning. Moving on, you will get up to speed with gradient descent variants, such as NAG, AMSGrad, AdaDelta, Adam, and Nadam. The book will then provide you with insights into recurrent neural networks (RNNs) and LSTM and how to generate song lyrics with RNN. Next, you will master the math necessary to work with convolutional and capsule networks, widely used for image recognition tasks. You will also learn how machines understand the semantics of words and documents using CBOW, skip-gram, and PV-DM. Finally, you will explore GANs, including InfoGAN and LSGAN, and autoencoders, such as contractive autoencoders and VAE. By the end of this book, you will be equipped with all the skills you need to implement deep learning in your own projects.