Numeric To Number
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SEBI Listing Obligations and Disclosure Requirements – A Handbook, 1e
Author: Dr. K. R. Chandratre
language: en
Publisher: Bloomsbury Publishing
Release Date: 2021-03-15
About the book The book provides detailed analysis of SEBI (Listing Obligations and Disclosure Requirements) Regulations, 2015 which replaced the Listing Agreement and were notified on 2nd September 2015. These Regulations impose considerable volume of compliance obligations on listed entities and every listed entity is obligated to comply with them. The volume of the Regulations and the pace at which they have been undergoing frequent changes makes the task of compliance a hard one for the compliance officers. This book attempts to simplify the complex mass of the Regulations and bring in the relevant provisions of the Companies Act, 2013 so as to assist the compliance officers in their task of compliance. These Regulations apply to the listed entity who has listed any of the following designated securities on recognised stock exchange(s): (a) Specified securities listed on main board or SME exchange or institutional trading platform; (b) Non-convertible debt securities, non-convertible redeemable preference shares, perpetual debt instrument, perpetual non-cumulative preference shares; (c) Indian depository receipts; (d) Securitised debt instruments; (e) Security receipts; (f) Units issued by mutual funds; (g) Any other securities as may be specified by the Board. It would be immensely useful for Company Secretaries, Law professionals & Chartered Accountants. Key highlights Covering detailed analysis of provisions applicable for listing of specified securities on recognized stock exchange(s). Topics have been thoroughly explained using judicial pronouncements.
Mastering Predictive Analytics with R
Author: James D. Miller
language: en
Publisher: Packt Publishing Ltd
Release Date: 2017-08-18
Master the craft of predictive modeling in R by developing strategy, intuition, and a solid foundation in essential concepts About This Book Grasping the major methods of predictive modeling and moving beyond black box thinking to a deeper level of understanding Leveraging the flexibility and modularity of R to experiment with a range of different techniques and data types Packed with practical advice and tips explaining important concepts and best practices to help you understand quickly and easily Who This Book Is For Although budding data scientists, predictive modelers, or quantitative analysts with only basic exposure to R and statistics will find this book to be useful, the experienced data scientist professional wishing to attain master level status , will also find this book extremely valuable.. This book assumes familiarity with the fundamentals of R, such as the main data types, simple functions, and how to move data around. Although no prior experience with machine learning or predictive modeling is required, there are some advanced topics provided that will require more than novice exposure. What You Will Learn Master the steps involved in the predictive modeling process Grow your expertise in using R and its diverse range of packages Learn how to classify predictive models and distinguish which models are suitable for a particular problem Understand steps for tidying data and improving the performing metrics Recognize the assumptions, strengths, and weaknesses of a predictive model Understand how and why each predictive model works in R Select appropriate metrics to assess the performance of different types of predictive model Explore word embedding and recurrent neural networks in R Train models in R that can work on very large datasets In Detail R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems. The book begins with a dedicated chapter on the language of models and the predictive modeling process. You will understand the learning curve and the process of tidying data. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real-world datasets. How do you train models that can handle really large datasets? This book will also show you just that. Finally, you will tackle the really important topic of deep learning by implementing applications on word embedding and recurrent neural networks. By the end of this book, you will have explored and tested the most popular modeling techniques in use on real- world datasets and mastered a diverse range of techniques in predictive analytics using R. Style and approach This book takes a step-by-step approach in explaining the intermediate to advanced concepts in predictive analytics. Every concept is explained in depth, supplemented with practical examples applicable in a real-world setting.
Cyber Security in Intelligent Computing and Communications
This book looks at cyber security challenges with topical advancements in computational intelligence and communication technologies. This book includes invited peer-reviewed chapters on the emerging intelligent computing and communication technology research advancements, experimental outcomes, and cyber security practices, threats, and attacks with challenges. The book begins with a state-of-the-art survey and reviews of cyber security trends and issues. It further covers areas such as developments in intelligent computing and communication, smart healthcare, agriculture, transportation, online education, and many more real-life applications using IoT, big data, cloud computing, artificial intelligence, data science, and machine learning. This book is of interest to graduate/postgraduate students, researchers, and academicians. This book will be a valuable resource for practitioners and professionals working in smart city visualization through secure and intelligent application design, development, deployment to foster digital revolution, and reliable integration of advanced computing and communication technologies with global significance.