The Colonel was inducted into the 1962 Indo-China Conflict as a freshly commissioned army officer in the 9 Gurkha Regiment. He saw through the 1962, 1965 & 1971 battles but passed away in 2004 after losing his battle with interstitial lung disease. He was the original blogger in a time when there was no Internet and very limited social media. Starting from 1989 onwards more than a thousand letters written by him were published in most Indian Newspapers .This book is a collection of Letters to the Editor edited and compiled by his son .It is in a small measure reliving a small portion of history, from Narsimha Rao to Vajpayee, from the Gulf War to Kargil. The book is not limited to the matters purely of the armed force. In fact more than fifty percent is on civic issues, environmental issues and many of the issues which touch every citizens life on a daily basis. Relive the tumultuous period of 1989 to 2004 through a collection of published articles and letters to the editor from a veteran soldier, environmentalist and civic activist.
This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.
Transformers are becoming a core part of many neural network architectures, employed in a wide range of applications such as NLP, Speech Recognition, Time Series, and Computer Vision. Transformers have gone through many adaptations and alterations, resulting in newer techniques and methods. Transformers for Machine Learning: A Deep Dive is the first comprehensive book on transformers. Key Features: A comprehensive reference book for detailed explanations for every algorithm and techniques related to the transformers. 60+ transformer architectures covered in a comprehensive manner. A book for understanding how to apply the transformer techniques in speech, text, time series, and computer vision. Practical tips and tricks for each architecture and how to use it in the real world. Hands-on case studies and code snippets for theory and practical real-world analysis using the tools and libraries, all ready to run in Google Colab. The theoretical explanations of the state-of-the-art transformer architectures will appeal to postgraduate students and researchers (academic and industry) as it will provide a single entry point with deep discussions of a quickly moving field. The practical hands-on case studies and code will appeal to undergraduate students, practitioners, and professionals as it allows for quick experimentation and lowers the barrier to entry into the field.
We take liberalism to be a set of ideas committed to political rights and self-determination, yet it also served to justify an empire built on political domination. Uday Mehta argues that imperialism, far from contradicting liberal tenets, in fact stemmed from liberal assumptions about reason and historical progress. Confronted with unfamiliar cultures such as India, British liberals could only see them as backward or infantile. In this, liberals manifested a narrow conception of human experience and ways of being in the world. Ironically, it is in the conservative Edmund Burke—a severe critic of Britain's arrogant, paternalistic colonial expansion—that Mehta finds an alternative and more capacious liberal vision. Shedding light on a fundamental tension in liberal theory, Liberalism and Empire reaches beyond post-colonial studies to revise our conception of the grand liberal tradition and the conception of experience with which it is associated.
Contributed articles on foreign relations of India post 1984 and national security concerns presented earlier at a seminar celebrating 40th anniversary of Institute for Defence Studies and Analyses.
This Brief provides a clear insight of the recent advances in the field of cancer theranostics with special emphasis upon nano scale carrier molecules (polymeric, protein and lipid based) and imaging agents (organic and inorganic).
Large Language Models (LLMs) have emerged as a cornerstone technology, transforming how we interact with information and redefining the boundaries of artificial intelligence. LLMs offer an unprecedented ability to understand, generate, and interact with human language in an intuitive and insightful manner, leading to transformative applications across domains like content creation, chatbots, search engines, and research tools. While fascinating, the complex workings of LLMs -- their intricate architecture, underlying algorithms, and ethical considerations -- require thorough exploration, creating a need for a comprehensive book on this subject. This book provides an authoritative exploration of the design, training, evolution, and application of LLMs. It begins with an overview of pre-trained language models and Transformer architectures, laying the groundwork for understanding prompt-based learning techniques. Next, it dives into methods for fine-tuning LLMs, integrating reinforcement learning for value alignment, and the convergence of LLMs with computer vision, robotics, and speech processing. The book strongly emphasizes practical applications, detailing real-world use cases such as conversational chatbots, retrieval-augmented generation (RAG), and code generation. These examples are carefully chosen to illustrate the diverse and impactful ways LLMs are being applied in various industries and scenarios. Readers will gain insights into operationalizing and deploying LLMs, from implementing modern tools and libraries to addressing challenges like bias and ethical implications. The book also introduces the cutting-edge realm of multimodal LLMs that can process audio, images, video, and robotic inputs. With hands-on tutorials for applying LLMs to natural language tasks, this thorough guide equips readers with both theoretical knowledge and practical skills for leveraging the full potential of large language models. This comprehensive resource is appropriate for a wide audience: students, researchers and academics in AI or NLP, practicing data scientists, and anyone looking to grasp the essence and intricacies of LLMs.
The Colonel was inducted into the 1962 Indo-China Conflict as a freshly commissioned army officer in the 9 Gurkha Regiment. He saw through the 1962, 1965 & 1971 battles but passed away in 2004 after losing his battle with interstitial lung disease. He was the original blogger in a time when there was no Internet and very limited social media. Starting from 1989 onwards more than a thousand letters written by him were published in most Indian Newspapers .This book is a collection of Letters to the Editor edited and compiled by his son .It is in a small measure reliving a small portion of history, from Narsimha Rao to Vajpayee, from the Gulf War to Kargil. The book is not limited to the matters purely of the armed force. In fact more than fifty percent is on civic issues, environmental issues and many of the issues which touch every citizens life on a daily basis. Relive the tumultuous period of 1989 to 2004 through a collection of published articles and letters to the editor from a veteran soldier, environmentalist and civic activist.
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