Computer Vision, Machine Learning, Artificial Intelligence 现在是应用越来越广泛了。大家是如何学习和应用的呢？ 这里有几本限时免费的电子书，抓紧时间领啊！ CS related: https://www.amazon.com/gp/product/B0DGDNXF54?ref_=dbs_m_mng_rwt_calw_tkin_2&storeType=ebooks: AI Genesis: Crafting Content with Generative Intelligence https://www.amazon.com/gp/product/B0B1L5WJR1?ref_=dbs_m_mng_rwt_calw_tkin_4&storeType=ebooks: Image Classification Using Python and Techniques of Computer Vision and Machine Learning: (Second Edition, Intermediate Version) https://www.amazon.com/gp/product/B0CW1FJHFH?ref_=dbs_m_mng_rwt_calw_tkin_1&storeType=ebooks: ChatGPT in Content Creation: Transforming Creativity with Artificial Intelligence and Revolutionizing the Creative Landscape https://www.amazon.com/gp/product/B09TFY9CPL?ref_=dbs_m_mng_rwt_calw_tkin_3&storeType=ebooks: Image Classification Using Python and Techniques of Computer Vision and Machine Learning: (Second Edition, Advanced Version) https://www.amazon.com/gp/product/B0CW1LP4TH?ref_=dbs_m_mng_rwt_calw_tkin_0&storeType=ebooks: ChatGPT Odyssey: Journeying Through the Wonders of AI Dialogue https://www.amazon.com/gp/product/B09GNLRSZX?ref_=dbs_m_mng_rwt_calw_tkin_0&storeType=ebooks: Image Classification Using Python and Techniques of Computer Vision and Machine Learning: Step-by-step Classifying Images with Python and Techniques of Computer Vision and Machine Learning https://www.amazon.com/gp/product/B07P6Z8V51?ref_=dbs_m_mng_rwt_calw_tkin_2&storeType=ebooks: Action Recognition: Step-by-step Recognizing Actions with Python and Recurrent Neural Network (Computer Vision and Machine Learning) https://www.amazon.com/gp/product/B07NKT94GV?ref_=dbs_m_mng_rwt_calw_tkin_1&storeType=ebooks: Image Classification: Step-by-step Classifying Images with Python and Techniques of Computer Vision and Machine Learning Others: https://www.amazon.com/gp/product/B08LBR8N42?ref_=dbs_m_mng_rwt_calw_tkin_1&storeType=ebooks: Kids Stories From Kid: Traveling https://www.amazon.com/gp/product/B08LB5XG63?ref_=dbs_m_mng_rwt_calw_tkin_1&storeType=ebooks: Kids Stories From Kid: Family https://www.amazon.com/gp/product/B0896Q5Q7T?ref_=dbs_m_mng_rwt_calw_tkin_1&storeType=ebooks: THE JOURNEY WEST
https://www.amazon.com/gp/product/B0DGDNXF54?ref_=dbs_m_mng_rwt_calw_tkin_2&storeType=ebooks: AI Genesis: Crafting Content with Generative Intelligence AI Genesis: Crafting Content with Generative Intelligence is your essential guide to the revolutionary world of generative AI, where technology meets creativity. Perfect for creatives, tech enthusiasts, and professionals, this book demystifies how AI can generate text, images, music, and even virtual worlds, transforming industries from design and entertainment to education and healthcare. What You'll Discover: Core Techniques: Dive into GANs, VAEs, and transformers, the algorithms powering generative AI. Real-World Applications: Learn how AI is reshaping content creation across various fields. Ethical Insights: Understand the responsibilities and challenges of using AI responsibly. Future Trends: Explore the next wave of innovations in AI-driven creativity. Whether you're looking to enhance your creative work with AI or simply want to stay ahead in the rapidly evolving tech landscape, AI Genesis provides the insights and tools you need to harness the power of generative AI. Start your journey into the future of content creation today!
https://www.amazon.com/gp/product/B0CW1FJHFH?ref_=dbs_m_mng_rwt_calw_tkin_1&storeType=ebooks: ChatGPT in Content Creation: Transforming Creativity with Artificial Intelligence and Revolutionizing the Creative Landscape "ChatGPT in Content Creation" is a groundbreaking guide that delves into the innovative world of using ChatGPT for digital content generation. This book offers a deep dive into the capabilities of ChatGPT, presenting a compelling narrative on how this cutting-edge technology is reshaping the landscape of content creation across various industries. Through insightful chapters, readers are introduced to the architecture of ChatGPT, its practical applications in content generation, and the ethical considerations that come with AI-driven creativity. From journalism to marketing, and entertainment, this book showcases the transformative power of ChatGPT, providing readers with practical strategies for leveraging AI to enhance their content creation processes. Designed for content creators, digital marketers, and technology enthusiasts, "ChatGPT in Content Creation" serves as both a primer for those new to AI and a comprehensive resource for professionals seeking to capitalize on the potential of ChatGPT. With real-world success stories, ethical guidelines, and future trends, this book is your gateway to mastering AI-generated content and pioneering innovation in your creative work.
https://www.amazon.com/gp/product/B0B1L5WJR1?ref_=dbs_m_mng_rwt_calw_tkin_4&storeType=ebooks: Image Classification Using Python and Techniques of Computer Vision and Machine Learning This book implemented six different algorithms to classify images with the prediction accuracy of the testing data as the primary criterion (the higher the better) and the time consumption as the secondary one (the shorter the better). The six algorithms are: Tiny Images Representation + Classifiers; HOG (Histogram of Oriented Gradients) Features Representation + Classifiers; Bag of SIFT (Scale Invariant Feature Transform) Features Representation + Classifiers; Training a CNN (Convolutional Neural Network) from scratch; Fine Tuning a Pre-Trained Deep Network (AlexNet); and Pre-Trained Deep Network (AlexNet) Features Representation + Classifiers. For the algorithms that use classifiers, two commonly used classifiers are implemented: the k-Nearest Neighbors (KNN) and the Support Vector Machines (SVM). The codes were written with Python in Jupyter Notebook, and they could be executed on both CPUs and GPUs. This book is a great project guidance for students in middle schools, high schools, and colleges.
https://www.amazon.com/gp/product/B07NKT94GV?ref_=dbs_m_mng_rwt_calw_tkin_1&storeType=ebooks: Image Classification: Step-by-step Classifying Images with Python and Techniques of Computer Vision and Machine Learning This book implemented six different algorithms to classify images with the prediction accuracy of the testing data as the primary criterion (the higher the better) and the time consumption as the secondary one (the shorter the better). The accuracies varied between about 30% and 90%, while the time consumptions varied from several seconds to more than one hour. Considering both of the criteria, the Pre-Trained AlexNet Features Representation plus a Classifier, such as the k-Nearest Neighbors (KNN) and the Support Vector Machines (SVM), was concluded as the best algorithm.The six algorithms are: Tiny Images Representation + Classifiers; HOG (Histogram of Oriented Gradients) Features Representation + Classifiers; Bag of SIFT (Scale Invariant Feature Transform) Features Representation + Classifiers; Training a CNN (Convolutional Neural Network) from scratch; Fine Tuning a Pre-Trained Deep Network (AlexNet); and Pre-Trained Deep Network (AlexNet) Features Representation + Classifiers.The codes were written with Python in Jupyter Notebook, and they could be executed on both CPUs and GPUs.
AI Genesis: Crafting Content with Generative Intelligence is your essential guide to the revolutionary world of generative AI, where technology meets creativity. Perfect for creatives, tech enthusiasts, and professionals, this book demystifies how AI can generate text, images, music, and even virtual worlds, transforming industries from design and entertainment to education and healthcare. What You'll Discover: Core Techniques: Dive into GANs, VAEs, and transformers, the algorithms powering generative AI. Real-World Applications: Learn how AI is reshaping content creation across various fields. Ethical Insights: Understand the responsibilities and challenges of using AI responsibly. Future Trends: Explore the next wave of innovations in AI-driven creativity. Whether you're looking to enhance your creative work with AI or simply want to stay ahead in the rapidly evolving tech landscape, AI Genesis provides the insights and tools you need to harness the power of generative AI. Start your journey into the future of content creation today!
"ChatGPT in Content Creation" is a groundbreaking guide that delves into the innovative world of using ChatGPT for digital content generation. This book offers a deep dive into the capabilities of ChatGPT, presenting a compelling narrative on how this cutting-edge technology is reshaping the landscape of content creation across various industries. Through insightful chapters, readers are introduced to the architecture of ChatGPT, its practical applications in content generation, and the ethical considerations that come with AI-driven creativity. From journalism to marketing, and entertainment, this book showcases the transformative power of ChatGPT, providing readers with practical strategies for leveraging AI to enhance their content creation processes. Designed for content creators, digital marketers, and technology enthusiasts, "ChatGPT in Content Creation" serves as both a primer for those new to AI and a comprehensive resource for professionals seeking to capitalize on the potential of ChatGPT. With real-world success stories, ethical guidelines, and future trends, this book is your gateway to mastering AI-generated content and pioneering innovation in your creative work.
This book implemented six different algorithms to classify images with the prediction accuracy of the testing data as the primary criterion (the higher the better) and the time consumption as the secondary one (the shorter the better). The six algorithms are: Tiny Images Representation + Classifiers; HOG (Histogram of Oriented Gradients) Features Representation + Classifiers; Bag of SIFT (Scale Invariant Feature Transform) Features Representation + Classifiers; Training a CNN (Convolutional Neural Network) from scratch; Fine Tuning a Pre-Trained Deep Network (AlexNet); and Pre-Trained Deep Network (AlexNet) Features Representation + Classifiers. For the algorithms that use classifiers, two commonly used classifiers are implemented: the k-Nearest Neighbors (KNN) and the Support Vector Machines (SVM). The codes were written with Python in Jupyter Notebook, and they could be executed on both CPUs and GPUs. This book is a great project guidance for students in middle schools, high schools, and colleges.
This book implemented six different algorithms to classify images with the prediction accuracy of the testing data as the primary criterion (the higher the better) and the time consumption as the secondary one (the shorter the better). The accuracies varied between about 30% and 90%, while the time consumptions varied from several seconds to more than one hour. Considering both of the criteria, the Pre-Trained AlexNet Features Representation plus a Classifier, such as the k-Nearest Neighbors (KNN) and the Support Vector Machines (SVM), was concluded as the best algorithm.The six algorithms are: Tiny Images Representation + Classifiers; HOG (Histogram of Oriented Gradients) Features Representation + Classifiers; Bag of SIFT (Scale Invariant Feature Transform) Features Representation + Classifiers; Training a CNN (Convolutional Neural Network) from scratch; Fine Tuning a Pre-Trained Deep Network (AlexNet); and Pre-Trained Deep Network (AlexNet) Features Representation + Classifiers.The codes were written with Python in Jupyter Notebook, and they could be executed on both CPUs and GPUs.