Outros livros que poderiam interessá-lo

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  "You're Not Doing It Right" -...

  Ellen Patnaude

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  In "You're Not Doing It Right," Ellen Patnaude bravely opens the door to the haunting reality of Lewy body dementia (LBD) and unravels its profound impact on families. One of the most common types of dementia after Alzheimer's disease, LBD is marked by fluctuations in cognition, hallucinations, and motor symptoms. The journey begins with subtle warnings of small changes in her mother's behavior that worry Patnaude's father, but go unnoticed by the author and her sibling. 
  Through heartfelt storytelling, Patnaude recounts her challenges in addressing the disturbing shifts in her mother's behavior and managing their long-standing, emotionally charged relationship. The pages unfold with raw honesty, detailing the struggles that ensure when a family is faced with a progressive, life-altering diagnosis. In contrast to the 'long goodbye' of Alzheimer's disease, LBD plunges Patnaude and her family into a roller coaster ride from hell. Every emotion is laid bare, from the initial denial to the desperate attempts to help and connect with a loved one slipping away. 
  Patnaude offers invaluable insights and lessons learned in the throes of this heartbreaking journey. With unwavering candor, she reflects on what might have made a difference for herself and her family members and shares the resources that may help other struggling families. She acknowledges the commonality of denial and the universal resistance to accepting a devastating diagnosis, especially when glimpses of normalcy persist. The relentless challenges of caring for someone with any type of dementia often lead to heightened stress, exhaustion, and severe emotional strain on caregivers. In this exploration of love, loss, and resilience, Patnaude extends a compassionate hand to those grappling with similar circumstances, offering solace and understanding within the pages of this deeply moving memoir.

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  Pattern Recognition and Machine...

  Chuck Sherman

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  "Pattern Recognition: Exploring the Power of Data Analysis and Prediction through Cutting-Edge Technology" is a comprehensive guide to the field of pattern recognition, written by a team of experts in the field. 
  The book covers the fundamentals of data analysis and statistical inference before delving into the theory and application of pattern recognition techniques. The authors explore a variety of methods, including statistical pattern recognition, machine learning, and deep learning, and provide practical examples of their use in computer vision, speech recognition, natural language processing, bioinformatics, finance, robotics, and automation. 
  Readers will learn about template matching, Fourier analysis and wavelets, feature extraction and selection, object recognition, image segmentation, texture analysis, and more. The book also covers supervised and unsupervised learning techniques, including linear regression and classification, decision trees, support vector machines, and clustering algorithms. 
  The authors discuss the potential impact of quantum computing on pattern recognition, as well as ethical considerations in the field. With its accessible writing style and detailed examples, "Pattern Recognition: Exploring the Power of Data Analysis and Prediction through Cutting-Edge Technology" is an essential resource for students, researchers, and practitioners interested in data analysis, machine learning, and artificial intelligence. 
   

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  The Art of Machine Learning -...

  Craig Dames

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  Machine learning is a subset of artificial intelligence that enables computers to learn from data and make decisions without being explicitly programmed. It is a field that has grown significantly over the past few decades, revolutionizing industries such as healthcare, finance, and technology. By leveraging algorithms and statistical models, machine learning systems can identify patterns, make predictions, and continuously improve their performance. 
  The foundation of machine learning lies in data. Without data, machine learning models cannot function effectively. Data can come in various forms, including structured numerical data, unstructured text, images, and audio. The process of training a machine learning model involves feeding it large amounts of data, allowing it to recognize relationships and make informed predictions. 
  Machine learning is broadly categorized into three types: supervised learning, unsupervised learning, and reinforcement learning. Supervised learning involves training a model on labeled data, where it learns to map inputs to outputs based on example pairs. This approach is commonly used in applications such as email spam detection and medical diagnosis. Unsupervised learning, on the other hand, deals with data that lacks labels. The model identifies patterns and structures within the data without prior guidance, making it useful for tasks like customer segmentation and anomaly detection. Reinforcement learning is a more dynamic approach where an agent learns to make decisions by interacting with an environment and receiving feedback in the form of rewards or penalties. This technique is widely used in robotics and game development.

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  Hothouse Earth - An Inhabitant's...

  Bill McGuire

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  'It's a paradox but this was one of the most chilling books I've read this year. It's the definitive guide to where we're heading' ANTHONY HOROWITZ
  
  
  'The Earth is already in a dangerous phase of heating. Many scientists admit privately to actually being "scared" by recent weather extremes. But the public doesn't like pessimism, so we environment journalists hint at future optimism. This book provides a more steely-eyed view on how we can cope with a hothouse world.' - ROGER HARRABIN, former BBC Environment Analyst
  
  
  'This accessible and authoritative book is a must-read for anyone who still thinks it could be OK to carry on as we are for a little bit longer, or that climate chaos might not affect them or their kids too badly.' MIKE BERNERS-LEE is a professor at Lancaster University, founder of Small World Consultancy and author of There is No Planet B: A Handbook for the Make or Break Years
  
  
  'If you read just one book about the menace of climate breakdown, make it this one.' - TIM RADFORD, Climate News Network
  
  
  We inhabit a planet in peril. Our once temperate world is locked on course to become a hothouse entirely of our own making.
  
  Hothouse Earth: An Inhabitant's Guide provides a post-COP26 perspective on the climate emergency, acknowledging that it is now practically impossible to keep this side of the 1.5°C dangerous climate change guardrail. The upshot is that we can no longer dodge the arrival of disastrous, all-pervasive, climate breakdown that will come as a hammer blow to global society and economy.
  
  
  Bill McGuire, Professor of Geophysical and Climate Hazards, explains the science behind the climate crisis and for the first time presents a blunt but authentic picture of the sort of world our children will grow old in, and our grandchildren grow up in; a world that we catch only glimpses of in today's blistering heatwaves, calamitous wildfires and ruinous floods and droughts. Bleak though it is, the picture is one we must all face up to, if only to spur genuine action - even at this late stage - to stop a harrowing future becoming a truly cataclysmic one.

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  Death to Beauty - The...

  Eugene M. Helveston

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  In the 1970s, Dr. Alan Scott sought to selectively weaken eye muscles to treat strabismus (when one or both eyes are misaligned) without surgery. After failed attempts with other agents, Scott developed a method to stabilize the bacteria that causes botulism, culminating in a drug that eventually became known as Botox. 
   
   
   
  In Death to Beauty, Eugene M. Helveston, MD, follows the unlikely story of botulism's 1817 discovery in contaminated German sausages, to its use in military and research facilities, to Scott, an ophthalmologist who aimed to safely use the drug in humans. Scott struggled alone as an unknown in the pharmaceutical industry, searching for clinical trial financing and FDA approval, which he achieved at a fraction of the billions big pharma usually spends to bring a drug to market. Eventually, the company Allergan bought him out, capitalizing on the possibilities for cosmetic uses. Scott's formula was renamed "Botox" and reached annual sales in the billions. After the sale, Scott received no further compensation from Botox sales and remained the same unassuming man. 
   
   
   
  A fascinating walk through the intricate history of how the world's deadliest toxin starting as a treatment for crossed eyes became a routine tool for the cosmetic industry, Death to Beauty will make you rethink success, beauty, and deadly bacteria.

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  Sweet and Deadly - How Coca-Cola...

  Murray Carpenter

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  If we knew that Coca-Cola was among the deadliest products in our diet, would we continue drinking it in such great quantities? The Coca-Cola Company has gone to extraordinary lengths to make sure we don't find out, as this damning exposé makes patently clear. Marshaling the findings of extensive research and deep investigative reporting, Murray Carpenter describes in Sweet and Deadly the damage Coke does to America's health—and the remarkable campaign of disinformation conducted by the company to keep consumers in the dark. 
   
   
   
  Sugar-sweetened beverages are the single item in the American diet that most contributes to the epidemic of chronic disease—in particular, obesity, type 2 diabetes, and cardiovascular disease—and Coca-Cola is America's favorite sugar-sweetened beverage, by far. Carpenter details how the Coca-Cola corporation's sophisticated shadow network has masterfully spread disinformation for decades to hide the health risks of its product from consumers—risks disproportionately borne by Black, brown, and low-income communities. Working from a playbook of obfuscation and pseudoscience that has worked well for other harmful products, from tobacco and trans fats to opioids, Coca-Cola has managed to maintain an aura of goodness and happiness. This eye-opening book finally and fully reveals the truth behind that aura.

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