In this book, the subject is developed from basics of components involved. Each concept is clearly depicted through illustrations. Programming has been carried out in C programming with Linux background. A set of quiz and review questions has been presented at the end of each chapter. The book covers various topics from the basic building blocks, design methodologies, modeling of embedded systems to layered approach in embedded systems, microcontrollers. The aim in writing this book is to make the readers aware of what an embedded system is all about, how it is constructed, challenges faced in this field and coding for it. The reader who is totally new to this subject can definitely opt for this book to get a feel for the subject.

• First book in the market covering Machine Learning concepts with practical implementation in oneAPI • oneAPI and the related toolkits are completely covered. • The ToC is fully comprehensive. • The AI analytics toolkit and the explanation is very novel and first of its kind. • The support materials and codes are to be made available in the GIT. • The video materials are also to be made available in the YouTube.

• First book in the market covering Machine Learning concepts with practical implementation in oneAPI • oneAPI and the related toolkits are completely covered. • The ToC is fully comprehensive. • The AI analytics toolkit and the explanation is very novel and first of its kind. • The support materials and codes are to be made available in the GIT. • The video materials are also to be made available in the YouTube.

The book augurs to be a mix of theoretical and practical perceptions of the related concepts pertaining to image processing. The primary objectives orient to offer an overview to the elementary concepts and practices appropriate to DIP as well as to provide theoretical exposition. It starts with an expanded coverage of the fundamentals to provide a more comprehensive and cohesive coverage of the topics including but not limited to: Applications and tools for image processing, fundamentals with several implementation examples Concepts of image formation, OpenCV installation with step-by-step screen shots Concepts behind intensity, brightness and contrast, color models Ways by which noises are created in an image and the possible remedial measures Edge detection, Image segmentation, classification, regression, Classification algorithms Importance of frequency domain in image processing field Relevant code snippets and the MATLAB codes, several interesting set of simple programs in OpenCV and Python to aid learning and for complete understanding The video lectures for specific topics through YouTube by the authors enable easy inference for the readers to apply the learnt theory into practice. The addition of contents at the end of each chapter such as quiz, review questions etc., fully prepares the readers for further study. Graduate Students, Post Graduate students, Researchers, and anyone in general interested in Image Processing, Computer Vision, Machine Learning domains etc. can find this book an excellent starting point for information and as an able ally.

Unique selling point: * This book teaches readers how to build IoT products through practical projects, ranging from beginners to advanced level, so that they can build knowledge through hands-on tasks rather than theoretical knowledge. Core audience: * IoT enthusiasts, students and tutors Place in the market: * This is a new approach and distinctly different from all of the books which focus only on theory.

This book intends to develop cyber awareness and technical knowledge in anyone who is interested in technology by looking at subjects and experiences the average person will have come into contact with in their life. This book aims to provide a complete and comprehensive analysis, technological inputs and case studies for the readers to build their awareness and knowledge, but in a meaningful way which will stay relevant. There are books available on the market, but they primarily discuss theory, and no industry connection or current state-of-the-art technology is presented. By discussing subjects and experiences that all readers will be familiar with, this book will aid understanding and comprehension of how cyber threats can be noticed, avoided and understood in everyday life. As well as case studies, this book also contains plentiful illustrations and supplementary videos, which will be available via YouTube to complement the information. Giri Govindarajulu is a Chief Information Security officer for Cisco Asiapac and is a 20-year Cisco veteran. Shyam Sundar Ramaswami is the Lead Threat Researcher with the Cisco Talos Threat Intelligence group. Shyam is a two-time TEDx speaker and a teacher of cybersecurity. Dr. Shriram K. Vasudevan is currently working as Dean of K. Ramakrishnan College of Technology. He has authored/co-authored 42 books for reputed publishers across the globe and 122 research papers in revered international journals, plus 30 papers for international/national conferences.

1) Focuses on the concepts and implementation strategies of various Deep Learning algorithms through properly curated examples. 2) The subject area will be valid for the next 10 years or so, as Deep Learning theory/algorithms and their applications will not be outdated easily. Hence there will be demand for such a book in the market. 3) In comparison to other titles, this book rigorously covers mathematical and conceptual details of relevant topics.

This book intends to develop cyber awareness and technical knowledge in anyone who is interested in technology by looking at subjects and experiences the average person will have come into contact with in their life. This book aims to provide a complete and comprehensive analysis, technological inputs and case studies for the readers to build their awareness and knowledge, but in a meaningful way which will stay relevant. There are books available on the market, but they primarily discuss theory, and no industry connection or current state-of-the-art technology is presented. By discussing subjects and experiences that all readers will be familiar with, this book will aid understanding and comprehension of how cyber threats can be noticed, avoided and understood in everyday life. As well as case studies, this book also contains plentiful illustrations and supplementary videos, which will be available via YouTube to complement the information. Giri Govindarajulu is a Chief Information Security officer for Cisco Asiapac and is a 20-year Cisco veteran. Shyam Sundar Ramaswami is the Lead Threat Researcher with the Cisco Talos Threat Intelligence group. Shyam is a two-time TEDx speaker and a teacher of cybersecurity. Dr. Shriram K. Vasudevan is currently working as Dean of K. Ramakrishnan College of Technology. He has authored/co-authored 42 books for reputed publishers across the globe and 122 research papers in revered international journals, plus 30 papers for international/national conferences.

Unique selling point: * This book teaches readers how to build IoT products through practical projects, ranging from beginners to advanced level, so that they can build knowledge through hands-on tasks rather than theoretical knowledge. Core audience: * IoT enthusiasts, students and tutors Place in the market: * This is a new approach and distinctly different from all of the books which focus only on theory.

Data Structures using Python provides an introduction to design, analysis, and implementation of data structures using the powerful language Python. This book is designed for a first course on the subject. It is written for the undergraduate engineering students of Computer Science, Information Technology and allied disciplines. The book begins with an overview of the concept, need, nomenclature followed by discussion of Arrays, Stacks, Queues, Double Ended Queues, Linked List - all under a chapter on Linear Data Structures. This is followed by a chapter on Non-linear Data Structures where Heap, Hash Table, Trie, and Disjoint Sets are discussed. Trees, though a non-linear data structure, is discussed as a separate chapter to emphasize upon its importance. The last few chapters of the book discusses Graphs, Searching, and Sorting finally ending with an appendix on Python built-in class functions.