{"product_id":"9781788394147","title":"Practical Convolutional Neural Networks: Implement advanced deep learning models using Python","description":"\u003cp\u003e\u003cb\u003eOne stop guide to implementing award-winning, and cutting-edge CNN architectures\u003c\/b\u003e\u003c\/p\u003e\u003cstrong\u003eKey Features\u003c\/strong\u003e\u003cul\u003e\n\u003cli\u003e[*]Fast-paced guide with use cases and real-world examples to get well versed with CNN techniques\u003c\/li\u003e\n\u003cli\u003e[*]Implement CNN models on image classification, transfer learning, Object Detection, Instance Segmentation, GANs and more\u003c\/li\u003e\n\u003cli\u003e[*]Implement powerful use-cases like image captioning, reinforcement learning for hard attention, and recurrent attention models\u003c\/li\u003e\n\u003c\/ul\u003e\u003cstrong\u003eBook Description\u003c\/strong\u003eConvolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, medical discoveries, innovative eCommerce and more. \u003cp\u003e\u003c\/p\u003eYou will learn to create innovative solutions around image and video analytics to solve complex machine learning and computer vision related problems and implement real-life CNN models. \u003cp\u003e\u003c\/p\u003eThis book starts with an overview of deep neural networkswith the example of image classification and walks you through building your first CNN for human face detector.  We will learn to use concepts like transfer learning with CNN, and Auto-Encoders to build very powerful models, even when not much of supervised training data of labeled images is available. \u003cp\u003e\u003c\/p\u003eLater we build upon the learning achieved to build advanced vision related algorithms for object detection, instance segmentation, generative adversarial networks, image captioning, attention mechanisms for vision, and recurrent models for vision. \u003cp\u003e\u003c\/p\u003eBy the end of this book, you should be ready to implement advanced, effective and efficient CNN models at your professional project or personal initiatives by working on complex image and video datasets.\u003cstrong\u003eWhat you will learn\u003c\/strong\u003e\u003cul\u003e\n\u003cli\u003eFrom CNN basic building blocks to advanced concepts understand practical areas they can be applied to\u003c\/li\u003e\n\u003cli\u003eBuild an image classifier CNN model to understand how different components interact with each other, and then learn how to optimize it\u003c\/li\u003e\n\u003cli\u003eLearn different algorithms that can be applied to Object Detection, and Instance Segmentation\u003c\/li\u003e\n\u003cli\u003eLearn advanced concepts like attention mechanisms for CNN to improve prediction accuracy\u003c\/li\u003e\n\u003cli\u003eUnderstand transfer learning and implement award-winning CNN architectures like AlexNet, VGG, GoogLeNet, ResNet and more\u003c\/li\u003e\n\u003cli\u003eUnderstand the working of generative adversarial networks and how it can create new, unseen images\u003c\/li\u003e\n\u003c\/ul\u003e\u003cstrong\u003eWho this book is for\u003c\/strong\u003e\u003cp\u003eThis book is for data scientists, machine learning and deep learning practitioners,  Cognitive and Artificial Intelligence enthusiasts who want to move one step further in building Convolutional Neural Networks. Get hands-on experience with extreme datasets and different CNN architectures to build efficient and smart ConvNet models. Basic knowledge of deep learning concepts and Python programming language is expected.\u003c\/p\u003e","brand":"Packt Publishing","offers":[{"title":"Default Title","offer_id":46465589838065,"sku":"9781788394147","price":30.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0674\/5433\/7265\/files\/9781788394147_p0.jpg?v=1765950923","url":"https:\/\/shop.barnesandnoble.com\/products\/9781788394147","provider":"Barnes \u0026 Noble","version":"1.0","type":"link"}