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  The Last Wilderness

  Murray Morgan, Tim McNulty

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  Murray Morgan's classic history of the Olympic Peninsula, originally published in 1955, evokes a remote American wilderness "as large as the state of Massachusetts, more rugged than the Rockies, its lowlands blanketed by a cool jungle of fir and pine and cedar, its peaks bearing hundreds of miles of living ice that gave rise to swift rivers alive with giant salmon." 
   
   
   
  Drawing on historical research and personal tales collected from docks, forest trails, and waterways, Morgan recounts vivid adventures of the area's settlers—loggers, hunters, prospectors, homesteaders, utopianists, murderers, profit-seekers, conservationists, Wobblies, and bureaucrats—alongside stories of coastal first peoples and striking descriptions of the peninsula's wildlife and land. 
   
   
   
  Freshly redesigned and with a new introduction by poet and environmentalist Tim McNulty, this humor-filled saga and landmark love story of one of the most formidably beautiful regions of the Pacific Northwest will inform and engage a new generation of listeners.

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  Fragmented - A Doctor's Quest to...

  MD Ilana Yurkiewicz

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  There's an unspoken assumption when we go to see a doctor: the doctor knows our medical story and is making decisions based on that story. But reality often falls short. Medical records vanish when we switch doctors. Critical details of life-saving treatment plans get lost in muddled electronic charts. The doctors we see change according to specialty, hospital shifts, or an insurer's whims. 
   
    
   
  In this gripping narrative from medicine's front lines, Ilana Yurkiewicz reveals how a system that doesn't talk to itself puts insupportable burdens on physicians, patients, and caregivers. The stories she tells are at once harrowing and commonplace. A patient narrowly averts an unnecessary, invasive heart procedure by producing a worn rhythm strip he has carried in his pocket for a decade. A man diagnosed with leukemia while visiting from abroad has thirty-one physicians, but no one he can call "his" doctor, with tragic consequences. When Yurkiewicz's own father falls ill, a culture that incentivizes health care providers to react with quick fixes leads to weeks of additional suffering. 
   
   
   
  The system is hanging by a thread, and we need better solutions. Yurkiewicz issues a clear-eyed call for change, naming concrete reforms doctors and policymakers can make, and empowering patients and their loved ones to advocate for themselves in the meantime.

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  Thinking 101 - How to Reason...

  Woo-kyoung Ahn

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  "Every day of our lives, we make judgments—and we don’t always do a very good job of it. Thinking 101 is an invaluable resource to anyone who wants to think better. In remarkably clear language, and with engaging and often funny examples, Woo-kyoung Ahn uses cutting-edge research to explain the mistakes we often make—and how to avoid them.”—Gretchen Rubin, #1 New York Times bestselling author of The Happiness Project and The Four Tendencies"Thinking 101 is a must-read—a smart and compellingly readable guide to cutting-edge research into how people think. Building from her popular Yale course, Professor Woo-kyoung Ahn shows how a better understanding of how our minds work can help us become smarter and wiser—and even kinder."—Paul Bloom, Professor of Psychology, University of Toronto, Brooks and Suzanne Professor Emeritus of Psychology at Yale University, and the author of The Sweet Spot"With an engaging and fresh narration, Lessa presents each fascinating chapter in a fun and easy way that helps listeners understand how to think more clearly and constructively."- AudioFilePsychologist Woo-kyoung Ahn devised a course at Yale called “Thinking” to help students examine the biases that cause so many problems in their daily lives. It quickly became one of the university’s most popular courses. Now, for the first time, Ahn presents key insights from her years of teaching and research in a book for everyone.She shows how “thinking problems” stand behind a wide range of challenges, from common, self-inflicted daily aggravations to our most pressing societal issues and inequities. Throughout, Ahn draws on decades of research from other cognitive psychologists, as well as from her own groundbreaking studies. And she presents it all in a compellingly accessible style that uses fun examples from pop culture, anecdotes from her own life, and illuminating stories from history and the headlines.Thinking 101 is an audiobook that goes far beyond other resources on thinking, showing how we can improve not just our own daily lives through better awareness of our biases but also the lives of everyone around us. It is, quite simply, required listening for everyone who wants to think—and live—better.A Macmillan Audio production from Flatiron Books

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  Machine Learning with Python -...

  Alexander Cane

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  Ways to combat retraining depend on the algorithm and consist of the correct values of the trainer's met parameters. In practice, model estimation is not performed on the same input data that was used to train the model. Divide 10-20% of all available data into a separate set and call it a set for evaluation. We will bring the other 10-20% into the set for ratification, and 60-80% of the remaining ones will be given to the trainer. The principle of data sharing depends on the data and the task. Random sampling is often a good method if inputs are independent of each other, and there is no strong imbalance between the number of positive and negative entries. 
  The intuitive analogy here is the same as with university studies: the teacher solves some problems with students in pairs and gives other’s similar tasks in the exam. What is important here (both in teaching students and models) is that these tasks are varied, and students cannot simply memorize the answers, and those who have mastered the material (similar tasks) will be able to repeat the thought process and answer correctly. 
  In machine learning, we split into data two sets: we will use the evaluation set to evaluate each model we train, using different approaches, algorithms, and model types to select the best one. That is, for each model, we will have two precision values - precision on the training dataset and precision on the evaluation dataset. It is normal for the former to be higher than the second, but not significantly. A big difference indicates retraining.

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  Deep sleep meditation Gentle...

  Sara Dylan

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  In this audio listening experience, Sara Dylan will be leading you gently into a quiet meditation while listening to gentle rainfall. You are sheltering from the rain and looking about as the rain falls. 
  You can choose what you see in your mind’s eye; you can look out at the rain as it falls or past the rain into the landscape; you can turn your head and look around and along the street or road. 
  "Rain is predictable, calming, stable, and non-threatening," says Dr Shelby Harris, a behavioural sleep-medicine specialist. According to Harris, steady rainfall noises help lull the brain into falling asleep, block outside noises, and frequently induce a more meditative state that brings on relaxation. 
  Gentle meditative music has been added to enhance your experience. 
   
  This deep sleep meditation has been designed as a sitting meditation to be used at any time of the day, but it works just as well when you are lying down. 
  Enjoy

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  Big Data for Beginners

  Tom Lesley

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  This audiobook is narrated by an AI Voice. In today’s digital world, data is everywhere — from social media and online shopping to healthcare, finance, and artificial intelligence. But what exactly is “Big Data,” and why is it transforming industries around the globe? 
   
  Big Data for Beginners is your clear, practical, and easy-to-follow guide to understanding the foundations of big data without complicated jargon or technical overload. Whether you are a student, entrepreneur, aspiring data analyst, IT professional, or simply curious about the future of technology, this book will help you build a strong understanding of how big data works and why it matters. 
   
  Inside this beginner-friendly guide, you will discover: 
   
  - What Big Data really is and how it is changing the modern world 
  - The key concepts behind data analytics, data science, and data engineering 
  - How companies use big data to improve decision-making and customer experiences 
  - The fundamentals of databases, cloud computing, machine learning, and AI 
  - Popular big data tools and technologies explained in simple terms 
  - Real-world applications in healthcare, business, marketing, finance, and cybersecurity 
  - Common challenges including privacy, security, and ethical concerns 
  - Career opportunities in the growing field of big data and analytics 
  - Practical tips for getting started with your own data journey 
   
  Designed specifically for beginners, this book breaks down complex ideas into simple explanations, real-life examples, and actionable insights that make learning engaging and accessible. 
   
  If you want to understand one of the most important technologies shaping the future, Big Data for Beginners is the perfect place to start.

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