Altri libri che potrebbero interessarti

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  Python for Machine Learning

  Jim D Johnston

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  Machine learning is fast becoming an important technique used by multiple industries, and in applications and research. But you don’t have to be part of a massive organization with an endless pot of money to get involved. 
  Even beginners using the Python programming language can be a part of machine learning, and that is what this book is for. Today, the only limit to machine learning is your imagination. In this book, I provide you with an overview of machine learning and some practical work to get your hands dirty. 
  Here’s what you will learn: 
  ·      Important machine learning concepts and applications 
  ·      The difference between supervised and unsupervised learning 
  ·      Commonly used supervised and unsupervised learning algorithms and models 
  ·      What libraries you will benefit from using 
  ·      How to visualize your data 
  ·      Regression and classification learning models 
  ·      An introduction to data science 
  ·      The five-step plan to becoming a data scientist 
  ·      Ten things that everyone needs to know about machine learning 
  You’ll even get a complete hands-on project that takes you through building your own machine learning project. 
  What you won't get is a lesson on using Python programming language; this book requires that you already know the basics. 
  So, if you are interested in taking your programming even further, scroll up, hit that Buy Now button, and start a new journey of discovery. 
   

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  Before the Machines Decide - Why...

  William R. Stanek

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  As artificial intelligence reshapes work, institutions, and everyday life, William R. Stanek argues that the most urgent question is not what machines can do, but what humans must become. Clear, accessible, and deeply human, this book offers a practical framework for resilience, ethics, creativity, and judgment in an age of accelerating AI.

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  Finding Genius: Understanding...

  Richard Jacobs

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  Richard Jacobs is a highly successful entrepreneur, accomplished podcast host, and author known for his significant contributions to various fields. As the founder of a research program and software platform, Richard has played a pivotal role in advancing groundbreaking work. 
  In October 2016, driven by a keen interest in emerging technologies such as artificial intelligence, 3D printing, regenerative medicine, Bitcoin, and blockchain, Richard embarked on a journey to unravel the mysteries of these fields. This passion culminated in the creation of the Future Tech Podcast. From the beginning, his goal was to find geniuses—the top 1% in their field who are almost impossible to reach from the outside. 
  Following a significant health crisis in 2017, Richard shifted his focus to health, medicine, and bioscience issues that impact us all, and the Finding Genius Podcast was born. His growing commitment to fostering understanding and innovation led him to establish the Finding Genius Foundation, a 501(c)(3) nonprofit supporting revolutionary research initiatives. 
  Driven by a mission to unearth transformative insights in the science of health and wellness, the foundation aims to make these insights accessible to everyday individuals who stand to benefit the most. Complementing this endeavor, Richard hosts two additional podcasts, The Good Question and Surviving Hard Times, both committed to delivering life-enriching and practical information. 
  Richard's extensive interviews with nearly 4,000 scientists, researchers, clinicians, CEOs, CSOs, entrepreneurs, and amateur scientists have resulted in a rich knowledge database and the Finding Genius book series, covering relevant and intriguing topics, including viruses, cancer, sleep health, and microplastics. This collection encompasses firsthand accounts of unique experiences and extraordinary insights.

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  Deepwater Alchemy - Extractive...

  Lisa Yin Han

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  How underwater mediation has transformed deep-sea spaces into resource-rich frontiers 
   
   
   
  Green energy technologies such as windmills, solar panels, and electric vehicles may soon depend on material found at the seabed. How did a space once imagined to be empty and unfathomable come to be thought of as a treasure trove of resources? Lisa Yin Han traces how contemporary developments in underwater sensing and imaging materially and imaginatively transmogrify the ocean bottom into a resource frontier capable of sustaining a digitally connected global future. 
   
   
   
  Set against the backdrop of climate change, energy transition, and the expansion of industrial offshore extractions, Deepwater Alchemy looks at oceanic media and its representation of the seabed in terms of valuable resources. From high-tech simulations to laboratories and archives that collect and analyze sediments, Han explores the media technologies that survey, visualize, and condition the possibility for industrial resource extraction, introducing the concept of extractive mediation to describe the conflations between resource prospecting and undersea knowledge production. Moving away from anthropocentric frameworks, she argues that we must equalize access to deep ocean mediation and include the submerged perspectives of multispecies communities.

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  Computer Networking: Network+...

  Richie Miller

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  If you want to PASS the CompTIA Network+ Certification, this book is for you! 
  GET THIS BOOK NOW AND START LEARNING TODAY!

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  Ultimate Transformer Models...

  Abhiram Ravikumar

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  Build Real-World AI with Transformers Powered by PyTorch 2.0.
  Book Description
  Transformer models have revolutionized AI across natural language processing, computer vision, and speech recognition. "Ultimate Transformer Models Using PyTorch 2.0" bridges theory and practice, guiding you from fundamentals to advanced implementations with hands-on projects that build a professional AI portfolio.
  This comprehensive journey spans 11 chapters, beginning with transformer foundations and PyTorch 2.0 setup. With this book, you will master self-attention mechanisms, tackle NLP tasks such as text classification and translation, and then expand into computer vision and speech processing. Advanced topics include BERT and GPT models, the Hugging Face ecosystem, training strategies, and deployment techniques. Each chapter features practical exercises that reinforce learning through real-world applications.
  By the end of this book, you will be able to confidently design, implement, and optimize transformer models for diverse challenges. So, whether revolutionizing language understanding, advancing computer vision, or innovating speech recognition, you will possess both theoretical knowledge and practical expertise to deploy solutions effectively across industries like healthcare, finance, and social media, positioning yourself at the AI revolution's forefront.
  Table of Contents
  1. Understanding the Evolution of Neural Networks
  2. Fundamentals of Transformer Architecture
  3. Getting Started with PyTorch
  4. 
  5. Natural Language Processing with Transformers
  6. Computer Vision with Transformers
  7. Speech Processing with Transformers
  8. Advanced Transformer Models
  9. Using HuggingFace with PyTorch
  10. Training and Fine-Tuning Transformers
  11. Deploying Transformer Models
  12. Transformers in Real-World Applications       
  
  Index

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