Other books that might interest you

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  Hands-on ML Projects with OpenCV

  Mugesh S.

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  Be at your A game in building Intelligent systems by leveraging Computer vision and Machine Learning. 
  
  KEY FEATURES 
  - Step-by-step instructions and code snippets for real world ML projects. 
  - Covers entire spectrum from basics to advanced concepts such as deep learning, transfer learning, and model optimization
  - Loaded with practical tips and best practices for implementing machine learning with OpenCV for optimising your workflow. 
  
  DESCRIPTION
  This book is an in-depth guide that merges machine learning techniques with OpenCV, the most popular computer vision library, using Python. The book introduces fundamental concepts in machine learning and computer vision, progressing to practical implementation with OpenCV. Concepts related to image preprocessing, contour and thresholding techniques, motion detection and tracking are explained in a step-by-step manner using code and output snippets. 
  
  Hands-on projects with real-world datasets will offer you an invaluable experience in solving OpenCV challenges with machine learning. It’s an ultimate guide to explore areas like deep learning, transfer learning, and model optimization, empowering readers to tackle complex tasks. Every chapter offers practical tips and tricks to build effective ML models. 
  
  By the end, you would have mastered and applied ML concepts confidently to real-world computer vision problems and will be able to develop robust and accurate machine-learning models for diverse applications. 
  
  Whether you are new to machine learning or seeking to enhance your computer vision skills, This book is an invaluable resource for mastering the integration of machine learning and computer vision using OpenCV and Python. 
  
  WHAT WILL YOU LEARN 
  - Learn how to work with images and perform basic image processing tasks using OpenCV. 
  - Implement machine learning techniques to computer vision tasks such as image classification, object detection, and image segmentation. 
  - Work on real-world projects and datasets to gain hands-on experience in applying machine learning techniques with OpenCV. 
  - Explore the concepts of deep learning using Tensorflow and Keras and how it can be used for computer vision tasks. 
  - Understand the concept of transfer learning and how pre-trained models can be leveraged for new tasks. 
  - Utilize techniques for model optimization and deployment in resource-constrained environments. 
  - Implement end-to-end solutions and address challenges encountered in practical scenarios. 
  
  WHO IS THIS BOOK FOR?
  This book is for everyone with a basic understanding of programming and who wants to apply machine learning in computer vision using OpenCV and Python. Whether you're a student, researcher, or developer, this book will equip you with practical skills for machine learning projects. Some familiarity with Python and machine learning concepts is assumed. Beginners too will find this book valuable as it offers clear examples and explanations for every concept. 
  
  TABLE OF CONTENTS 
  Chapter 1: Getting Started With OpenCV 
  Chapter 2: Basic Image & Video Analytics in OpenCV
  Chapter 3: Image Processing 1 using OpenCV
  Chapter 4: Image Processing 2 using OpenCV
  Chapter 5: Thresholding and Contour Techniques Using OpenCV 
  Chapter 6: Detect Corners and Road Lane using OpenCV
  Chapter 7: Object And Motion Detection Using Opencv
  Chapter 8: Image Segmentation and Detecting Faces Using OpenCV
  Chapter 9: Introduction to Deep Learning with OpenCV
  Chapter 10: Advance Deep Learning Projects with OpenCV
  Chapter 11: Deployment of OpenCV projects

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  Introduction to Quantum Field...

  Mark Hedges

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  Quantum Field Theory (QFT) is the framework that unifies quantum mechanics and special relativity, providing a theoretical foundation for describing fundamental particles and their interactions. Unlike quantum mechanics, which describes particles as wavefunctions evolving in time, QFT treats particles as excitations of underlying fields that pervade all of space. This shift in perspective is necessary to accommodate relativistic effects and to describe processes such as particle creation and annihilation, which are not possible in non-relativistic quantum mechanics. 
  The motivation for QFT arises from the limitations of single-particle quantum mechanics when applied to high-energy physics. In relativistic systems, particles can be created and destroyed in interactions, as seen in high-energy collisions and radioactive decays. Traditional quantum mechanics, which treats particles as fixed entities, cannot account for such processes. By formulating particles as field excitations, QFT allows for a consistent description of multi-particle interactions and naturally incorporates the principles of special relativity. 
  At its core, QFT extends the principles of classical field theory to quantum systems. Classical field theories, such as Maxwell’s electrodynamics, describe how physical quantities vary across space and time. In QFT, these fields are quantized, meaning that their excitations correspond to discrete particles. The simplest example is the Klein-Gordon field, which describes spin-zero particles like mesons. The quantization of this field leads to the interpretation of its solutions as particle states, obeying relativistic energy-momentum relations.

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  The UFO Experience - Evidence...

  J. Allen Hynek

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  Cited by the New York Review of Books as “the best brief for visitation,” this classic study presents an analysis of UFO reports and concludes that many sightings cannot be easily dismissed. The case against UFOs and unidentified aerial phenomena (UAP) has not been put to rest. Although UFOs “officially” did not exist for decades according to the government, reports of sightings continue to be made, and the latest releases from the government and related hearings have surprised the world. While the scientific community has put UFOs out to pasture, the evidence used to dismiss them is rare and unscientific. Dr. Hynek, a scientist himself, and the only government-paid ufologist in history, looks at the decisions made by officialdom in the early days of ufology and how these decisions have held us back—to the point that we are still naively talking about UFOs as we were in the 1950s. Has seventy years of research made no difference at all in our understanding? Dr. Hynek proves that there is a conspiracy afoot to hide the facts and that there are many cases that still need to be explained by mainstream science—not dismissed with facile jokes and stupid logic. Citing specific cases, Hynek challenges those in the ivory tower by raising questions that have still not been answered and refuting mainstream arguments that have yet to be proven. 

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  Advabced Scrum Case Studies Vol...

  Frederik Mark Fowler

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  You are an Agile Coach and you are being called in to fix a problem with project ownership.  There is a team of developers who look good on paper but who are not performing up to expectations.  They do not seem to care very much about the work they are doing.  You have been asked to figure out what is wrong and to fix it. 
  What should you do? 
  This case and the others in the series come from the real-world experiences of a group of Scrum professionals who meet regularly to discuss the Scrum Framework and how to apply it to actual situations they have encountered.  These discussions have been led since 2015 by Frederik Mark Fowler, A Doctor of Scrum and Holder of the Professional Scrum Master level III certification awarded by Scrum.org.  Fred has worked with the Scrum Framework for almost 20 years and has trained more then 300 people to become Scrum Masters and Product Owners.  For more information, visit www.Patreon.com/SiliconValleyScrum.

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  Mastering Data Science and...

  Finnley Harper

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  "Mastering Data Science and Analytics: The Power of Data: From Analysis to Action in the Modern World" is a comprehensive guide that illuminates the transformative potential of data in today's digital age. This book is invaluable for people and organizations looking to fully utilize data to support well-informed decision-making and accomplish strategic goals.  
  From the foundational principles of data science to advanced analytical techniques, each chapter offers a systematic approach to understanding and applying key concepts. This practical approach ensures that readers not only learn the theory but also gain the skills to collect, clean, analyze, and visualize data effectively. These skills will provide valuable insights into patterns, trends, and relationships that can inform strategic initiatives and drive organizational success. 
  This book demonstrates the tangible impact of data science and analytics across various industries and domains through real-world case studies and practical examples. Whether you're a seasoned data professional looking to deepen your expertise or a novice eager to embark on a journey into the world of data, this book provides the knowledge and tools needed to thrive in today's data-driven landscape. 
  Moreover, this book is about more than just data science and analytics. It's about doing it right. The significance of ethical deliberations and conscientious data practices is underscored, guaranteeing that readers approach data science with honesty and awareness of the wider societal consequences. By mastering data analytics, readers can drive innovation, unlock new opportunities, and design a brighter future in the modern world—all while adhering to ethical norms.

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  Moral Philosophy - Navigating...

  Hector Davidson

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  Moral philosophy, or ethics, is the branch of philosophy that examines concepts of right and wrong, virtue and vice, justice and injustice. It seeks to understand the foundations of moral principles, how they are applied in human life, and whether moral truths are objective or subjective. From ancient civilizations to modern societies, moral philosophy has played a crucial role in shaping human thought, behavior, and institutions. 
  One of the fundamental questions in moral philosophy is whether morality is a product of reason, emotion, or social convention. Some philosophers argue that moral principles stem from rational deliberation, while others suggest that morality is deeply tied to human emotions, such as compassion and guilt. Social constructivists, on the other hand, emphasize that moral norms evolve through cultural traditions, religious beliefs, and historical contexts. 
  The study of moral philosophy is often divided into three main branches. Meta-ethics explores the nature and meaning of moral language, questioning whether moral statements express objective truths or subjective opinions. Normative ethics examines different ethical theories that propose principles for moral conduct, such as consequentialism, deontology, and virtue ethics. Applied ethics focuses on practical moral issues, including debates on human rights, justice, medical ethics, and environmental concerns.

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