Otros libros que te pueden interesar

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  2047 - Fictional Stories of...

  Dr. Jawahar Surisetti

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  "2047" by eminent futurist and psychologist Dr Jawahar Surisetti, offers a compelling glimpse into India's future, a century after gaining independence. Through interconnected stories, it paints a vivid picture of India's global prominence. showcasing its technological supremacy, robust healthcare and education systems, sustainable agriculture practices, pioneering space exploration endeavours, modern infrastructure, and efficient transportation networks. Each narrative thread illuminates India's ascent as a superpower, emphasising its leadership in various fields while highlighting the nation's commitment to progress, innovation, and inclusive development. "2047" celebrates India's journey towards prosperity and influence on the world stage, offering a hopeful vision of the nation's future achievements.

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  ChatGPT talks on science for...

  Paulo Dario

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  This book follows a series of "conversations" with these tools, mainly with "chatGPT 4.0" but also with "Bard". It's well known that chatGPT is hampered in its research up to a certain point in time and, because they are language modeling tools, they end up inventing... a lot, especially in bibliographic references. However, accessory tools are emerging that make it possible to improve and even correct this situation, tools that will certainly become much more powerful in the future, but which are already a reality. So, using all these AI tools, a book has been created that aims to be a pedagogical tool that answers a series of questions that can be asked by secondary and higher education students, or even people who are just interested in these issues, but who don't have the access or predisposition to use these types of AI tools.

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  A Dumb Birds Field Guide to the...

  Matt Kracht

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  We can all agree—birds are terrible. They're stupid and won't shut up. 
   
   
   
  Featuring fifty of the absolute worst birds to fly the earth, Kracht identifies each of their most terrible qualities, details exactly why they suck, and shows you why. Including all-new, all-worst fowl, such as: the absolute waste of feathers Cruddy Turdstone (Ruddy Turnstone), the utter a-hole Blank Staring-Eyes Flycrapper (Black Paradise Flycatcher), the outright loser Dowdy Woodfucker (Downy Woodpecker), and many more! 
   
   
   
  Even the author's previous bird takedown guides are no preparation for this hilariously harrowing collection of squawking, conceited, trash-eating, and even murderous idiots. The horror. The horror . . . 
   
   
   
  LOVE BIRDS? HATE BIRDS?: For those who hate birds and for bird lovers everywhere with a sense of humor, this handbook is equal parts profane and funny, and—let's face it—true. 
   
   
   
  ENTERTAINING AND EDUCATIONAL: This uproarious guide to all things wings includes tips for bird identification, musings on the avian population and classification, and more. Plus, each entry is accompanied by facts about a bird's (annoying) call, its (dumb) migratory pattern, its (downright tacky) markings, and more.

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  A Fascinating Journey Through...

  Martin K. Ettington

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  Time is a fascinating subject and one which affects our lives in many ways.  
  This book covers a lot of aspects of the subject. 
  First, how did measurements of time like seconds, minutes, hours, and years develop? 
  Next, what is the history of timekeeping mechanisms from ancient water clocks, to mechanical mechanisms, atomic clocks, and much more. 
  Lastly, what are some of the stranger aspects or anomalies of time such as premonitions, how time and space work, and possible time travel stories. 
  And philosophical questions like: Does the future already exist? 
  I wanted this book to be a comprehensive volume on time and so included lots of different stories and understandings about time which indicate we may not fully understand it yet.

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  The Honey Trap - How the Good...

  Dana L. Church

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  The last decade has seen an explosion of urban beekeeping in the US, Canada, and Europe, a well-intentioned response to perceived threats to the global honey bee population. Many thousands of people have taken up this seemingly environmentally friendly hobby, tending backyard and rooftop hives (or paying a company to do so) and encouraging honey bees to make honey and pollinate flowers. What could be wrong with that? 
   
   
   
  Quite a lot, in fact. In The Honey Trap, scientist and author Dana Church demonstrates that despite reports to the contrary, honey bees are nowhere near extinction. Rather, their nurturing by urban beekeepers is having far-reaching and potentially devastating consequences for the 19,999 other species of bees on the planet, with knock-on effects for plants, both cultivated and wild, and our ecosystems more generally. 
   
   
   
  With engaging storytelling and a wealth of knowledge about bees and their ways, Church unravels the complexities of human interactions with our winged friends and demonstrates how dangerously selfish our thinking can be. It's a wake-up call for humanity to embrace sustainable practices and protect these vital pollinators before it's too late.

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  Low-Code AI - A Practical...

  Michael Abel, Gwendolyn Stripling

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  Take a data-first and use-case-driven approach with Low-Code AI to understand machine learning and deep learning concepts. This hands-on guide presents three problem-focused ways to learn no-code ML using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. In each case, you'll learn key ML concepts by using real-world datasets with realistic problems. 
   
   
   
  Business and data analysts get a project-based introduction to ML/AI using a detailed, data-driven approach: loading and analyzing data; feeding data into an ML model; building, training, and testing; and deploying the model into production. Authors Michael Abel and Gwendolyn Stripling show you how to build machine learning models for retail, healthcare, financial services, energy, and telecommunications. 
   
   
   
  You'll learn how to distinguish between structured and unstructured data and the challenges they present; visualize and analyze data; preprocess data for input into a machine learning model; differentiate between the regression and classification supervised learning models; compare different ML model types and architectures, from no code to low code to custom training; design, implement, and tune ML models; and export data to a GitHub repository for data management and governance.

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