This book presents a framework for integrating blended learning and massive open online courses (MOOCs) in the Indian education system. It argues that blended teaching and learning is the most suitable approach to education in a post-COVID-19 world. Drawing on case studies used in blended learning practices around the world, the book provides ample resources for beginners to improvise the spread of knowledge around information technology in higher education. It discusses various concepts such as flip learning in blended learning models and examines the self-assessment tools and structures it offers to institutions for building competencies. In addition to addressing the challenges and opportunities of adopting the digital mode of teaching, the book also offers techniques and concepts helpful for designing MOOCs. It covers concepts such as curriculum designing, content flow, teaching behavior, and evaluation patterns, which are important aspects of online teaching. An indispensable guide to navigating the shift from offline to online teaching, this book will be of interest to students, teachers, and researchers of education, education technology, digital education, and information technology. It will also be useful to policymakers, educational institutions, EdTech start-ups, NGOs in the education sector, and online education centers.

This book presents a framework for integrating blended learning and massive open online courses (MOOCs) in the Indian education system. It argues that blended teaching and learning is the most suitable approach to education in a post-COVID-19 world. Drawing on case studies used in blended learning practices around the world, the book provides ample resources for beginners to improvise the spread of knowledge around information technology in higher education. It discusses various concepts such as flip learning in blended learning models and examines the self-assessment tools and structures it offers to institutions for building competencies. In addition to addressing the challenges and opportunities of adopting the digital mode of teaching, the book also offers techniques and concepts helpful for designing MOOCs. It covers concepts such as curriculum designing, content flow, teaching behavior, and evaluation patterns, which are important aspects of online teaching. An indispensable guide to navigating the shift from offline to online teaching, this book will be of interest to students, teachers, and researchers of education, education technology, digital education, and information technology. It will also be useful to policymakers, educational institutions, EdTech start-ups, NGOs in the education sector, and online education centers.

The primary goal of this book is to address the issues faced by teachers in the adoption of digital tools into their teaching and their students learning. This book also addresses the issues confronting educators in the integration of digital technologies into their teaching and their students' learning. Such issues include a skepticism of the added value of technology to educational learning outcomes, the perception of the requirement to keep up with the fast pace of technological innovation, a lack of knowledge of affordable educational digital tools and a lack of understanding of pedagogical strategies to embrace digital technologies in their teaching. This book presents theoretical perspectives of learning and teaching today's digital students with technology and proposes a pragmatic and sustainable framework for teachers' professional learning to embed digital technologies into their repertoire of teaching strategies in a systematic, coherent and comfortable manner so that technology integration becomes an almost effortless pedagogy in their day-to-day teaching. Some of the objectives are given below: Shares valuable insights into the influence of technology on teaching and learning in higher education Provides deeper insights on higher education and sustainability interact Studies innovations from various perspectives Investigates how the educators and students apply the unique innovative and emotional dimensions in modern age of learning Provides a timely overview of changes in education reforms and policy research globally Evaluates the problematic relationship between globalization, the state, and education reforms.

This book presents select proceedings of the International Conference on Advances in Sustainable Technologies (ICAST 2020), organized by Lovely Professional University, Punjab, India. The topics covered include computer aided design (CAD), computer assisted manufacturing (CAM), computer integrated manufacturing (CIM), computer aided engineering (CAE) and product design, dynamics of control structures and systems, solid mechanics: differential and dynamical systems, modelling and simulation. The book also discusses various modern age design tools including finite element analysis, modelling, analysis and simulation of manufacturing processes, process design, automation, mechatronics, robotics and assembly, etc. The book will be useful for beginners, researchers, and professionals interested in the field of sustainable design practices.

This book introduces the theory of enveloping semigroups-an important tool in the field of topological dynamics-introduced by Robert Ellis. The book deals with the basic theory of topological dynamics and touches on the advanced concepts of the dynamics of induced systems and their enveloping semigroups. All the chapters in the book are well organized and systematically dealing with introductory topics through advanced research topics. The basic concepts give the motivation to begin with, then the theory, and finally the new research-oriented topics. The results are presented with detailed proof, plenty of examples and several open questions are put forward to motivate for future research. Some of the results, related to the enveloping semigroup, are new to the existing literature. The enveloping semigroups of the induced systems is considered for the first time in the literature, and some new results are obtained. The book has a research-oriented flavour in the field of topological dynamics.

Computational analysis of natural science experiments often confronts noisy data due to natural variability in environment or measurement. Drawing conclusions in the face of such noise entails a statistical analysis. Parametric statistical methods assume that the data is a sample from a population that can be characterized by a specific distribution (e.g., a normal distribution). When the assumption is true, parametric approaches can lead to high confidence predictions. However, in many cases particular distribution assumptions do not hold. In that case, assuming a distribution may yield false conclusions. The companion book Statistics is Easy, gave a (nearly) equation-free introduction to nonparametric (i.e., no distribution assumption) statistical methods. The present book applies data preparation, machine learning, and nonparametric statistics to three quite different life science datasets. We provide the code as applied to each dataset in both R and Python 3. We also include exercises for self-study or classroom use.

To get ahead in today's hyper-competitive marketplace, your business has to take advantage of the data you already have and mine that data to give you new insight, metrics, and clues to what drives successful customer interactions. In Pro SharePoint 2013 Business Intelligence Solutions, you'll learn exactly how to unlock that magic, build business intelligence facilities on SharePoint, and glean insights from data to propel your business to the next level. To understand the various business intelligence offerings in SharePoint 2013, you need to understand the core SQL Server business intelligence concepts, and the first part of the book presents a comprehensive tutorial on those fundamentals.Pro SharePoint 2013 Business Intelligence Solutions then focuses on specific SharePoint business intelligence investments including: * Visio Services * Excel Services * SQL Server Reporting Services * Business Connectivity Services * Power View and PerformancePoint Services Authors Manpreet Singh, Sha Anandan, Sahil Malik, and Steve Wright walk you through all of this material comprehensively in practical, hands-on format, with plenty of examples to empower you to use these products in your real-life projects. As compelling as SharePoint and SQL Server business intelligence are together, the challenge always has been finding people who understand both SharePoint and SQL Server well enough to deliver such business intelligence solutions. With this book in hand, you become part of that select group. Get your copy of Pro SharePoint 2013 Business Intelligence Solutions today What you'll learn * Understand the fundamentals and framework of business intelligence. * Learn how to integrate Visio Services, and discover the developer story. * Practice working with the Secure Store Service.* Experience authoring and publishing reports using Report Builder and how to re-purpose published reports in Reporting Services. * Glean practical advice about deploying and developing for Power View and PerformancePoint Services in SharePoint 2013. * Learn about the advances in Excel Services and PowerPivot, and their application within SharePoint to practical situations. * Gain a deep understanding of the Business Data Services feature set in SharePoint 2013. Who this book is for Pro SharePoint 2013 Business Intelligence Solutions offers SharePoint developers an essential BI foundation experience and an introduction to SQL Server 2012 tools for business intelligence. This book will also benefit SQL Server developers and administrators who require knowledge of setting up the basic infrastructure on the SharePoint platform for business intelligence.

Leverage the power of deep learning and Keras to develop smarter and more efficient data models Key Features Understand different neural networks and their implementation using Keras Explore recipes for training and fine-tuning your neural network models Put your deep learning knowledge to practice with real-world use-cases, tips, and tricks Book DescriptionKeras has quickly emerged as a popular deep learning library. Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and accuracy. The Keras Deep Learning Cookbook shows you how to tackle different problems encountered while training efficient deep learning models, with the help of the popular Keras library. Starting with installing and setting up Keras, the book demonstrates how you can perform deep learning with Keras in the TensorFlow. From loading data to fitting and evaluating your model for optimal performance, you will work through a step-by-step process to tackle every possible problem faced while training deep models. You will implement convolutional and recurrent neural networks, adversarial networks, and more with the help of this handy guide. In addition to this, you will learn how to train these models for real-world image and language processing tasks. By the end of this book, you will have a practical, hands-on understanding of how you can leverage the power of Python and Keras to perform effective deep learning What you will learn Install and configure Keras in TensorFlow Master neural network programming using the Keras library Understand the different Keras layers Use Keras to implement simple feed-forward neural networks, CNNs and RNNs Work with various datasets and models used for image and text classification Develop text summarization and reinforcement learning models using Keras Who this book is forKeras Deep Learning Cookbook is for you if you are a data scientist or machine learning expert who wants to find practical solutions to common problems encountered while training deep learning models. A basic understanding of Python and some experience in machine learning and neural networks is required for this book.

Develop and manage effective real-time streaming solutions by leveraging the power of Microsoft Azure About This Book * Analyze your data from various sources using Microsoft Azure Stream Analytics * Develop, manage and automate your stream analytics solution with Microsoft Azure * A practical guide to real-time event processing and performing analytics on the cloud Who This Book Is For If you are looking for a resource that teaches you how to process continuous streams of data in real-time, this book is what you need. A basic understanding of the concepts in analytics is all you need to get started with this book What You Will Learn * Perform real-time event processing with Azure Stream Analysis * Incorporate the features of Big Data Lambda architecture pattern in real-time data processing * Design a streaming pipeline for storage and batch analysis * Implement data transformation and computation activities over stream of events * Automate your streaming pipeline using Powershell and the .NET SDK * Integrate your streaming pipeline with popular Machine Learning and Predictive Analytics modelling algorithms * Monitor and troubleshoot your Azure Streaming jobs effectively In Detail Microsoft Azure is a very popular cloud computing service used by many organizations around the world. Its latest analytics offering, Stream Analytics, allows you to process and get actionable insights from different kinds of data in real-time. This book is your guide to understanding the basics of how Azure Stream Analytics works, and building your own analytics solution using its capabilities. You will start with understanding what Stream Analytics is, and why it is a popular choice for getting real-time insights from data. Then, you will be introduced to Azure Stream Analytics, and see how you can use the tools and functions in Azure to develop your own Streaming Analytics. Over the course of the book, you will be given comparative analytic guidance on using Azure Streaming with other Microsoft Data Platform resources such as Big Data Lambda Architecture integration for real time data analysis and differences of scenarios for architecture designing with Azure HDInsight Hadoop clusters with Storm or Stream Analytics. The book also shows you how you can manage, monitor, and scale your solution for optimal performance. By the end of this book, you will be well-versed in using Azure Stream Analytics to develop an efficient analytics solution that can work with any type of data. Style and approach A comprehensive guidance on developing real-time event processing with Azure Stream Analysis

Neural Networks and their implementation decoded with TensorFlow About This Book * Develop a strong background in neural network programming from scratch, using the popular Tensorflow library. * Use Tensorflow to implement different kinds of neural networks - from simple feedforward neural networks to multilayered perceptrons, CNNs, RNNs and more. * A highly practical guide including real-world datasets and use-cases to simplify your understanding of neural networks and their implementation. Who This Book Is For This book is meant for developers with a statistical background who want to work with neural networks. Though we will be using TensorFlow as the underlying library for neural networks, book can be used as a generic resource to bridge the gap between the math and the implementation of deep learning. If you have some understanding of Tensorflow and Python and want to learn what happens at a level lower than the plain API syntax, this book is for you. What You Will Learn * Learn Linear Algebra and mathematics behind neural network. * Dive deep into Neural networks from the basic to advanced concepts like CNN, RNN Deep Belief Networks, Deep Feedforward Networks. * Explore Optimization techniques for solving problems like Local minima, Global minima, Saddle points * Learn through real world examples like Sentiment Analysis. * Train different types of generative models and explore autoencoders. * Explore TensorFlow as an example of deep learning implementation. In Detail If you're aware of the buzz surrounding the terms such as "machine learning," "artificial intelligence," or "deep learning," you might know what neural networks are. Ever wondered how they help in solving complex computational problem efficiently, or how to train efficient neural networks? This book will teach you just that. You will start by getting a quick overview of the popular TensorFlow library and how it is used to train different neural networks. You will get a thorough understanding of the fundamentals and basic math for neural networks and why TensorFlow is a popular choice Then, you will proceed to implement a simple feed forward neural network. Next you will master optimization techniques and algorithms for neural networks using TensorFlow. Further, you will learn to implement some more complex types of neural networks such as convolutional neural networks, recurrent neural networks, and Deep Belief Networks. In the course of the book, you will be working on real-world datasets to get a hands-on understanding of neural network programming. You will also get to train generative models and will learn the applications of autoencoders. By the end of this book, you will have a fair understanding of how you can leverage the power of TensorFlow to train neural networks of varying complexities, without any hassle. While you are learning about various neural network implementations you will learn the underlying mathematics and linear algebra and how they map to the appropriate TensorFlow constructs. Style and Approach This book is designed to give you just the right number of concepts to back up the examples. With real-world use cases and problems solved, this book is a handy guide for you. Each concept is backed by a generic and real-world problem, followed by a variation, making you independent and able to solve any problem with neural networks. All of the content is demystified by a simple and straightforward approach.

This book provides a modern, self-contained, introduction to DBMS. We designed the book to be used by both learners desiring a firm foundation to build on, and practitioners in search of critical analysis and modern implementations of the most important DBMS system. This book is written in simple English language which is easily understandable by student's who first language is not an English Language. The Authors of this book Manpreet Singh Bhullar and Sumeet kumar have more than 9 year experience in teaching.