{"product_id":"2940163550531","title":"Convolutional Neural Networks in Python: Beginner's Guide to Convolutional Neural Networks in Python","description":"\u003cp\u003eThis book covers the basics behind Convolutional Neural Networks by introducing you to this complex world of deep learning and artificial neural networks in a simple and easy to understand way. It is perfect for any beginner out there looking forward to learning more about this machine learning field.This book is all about how to use convolutional neural networks for various image, object and other common classification problems in Python. Here, we also take a deeper look into various Keras layer used for building CNNs we take a look at different activation functions and much more, which will eventually lead you to creating highly accurate models able of performing great task results on various image classification, object classification and other problems.Therefore, at the end of the book, you will have a better insight into this world, thus you will be more than prepared to deal with more complex and challenging tasks on your own.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eHere Is a Preview of What You'll Learn In This Book…\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eConvolutional neural networks structure\u003c\/li\u003e\n\u003cli\u003eHow convolutional neural networks actually work\u003c\/li\u003e\n\u003cli\u003eConvolutional neural networks applications\u003c\/li\u003e\n\u003cli\u003eThe importance of convolution operator\u003c\/li\u003e\n\u003cli\u003eDifferent convolutional neural networks layers and their importance\u003c\/li\u003e\n\u003cli\u003eArrangement of spatial parameters\u003c\/li\u003e\n\u003cli\u003eHow and when to use stride and zero-padding\u003c\/li\u003e\n\u003cli\u003eMethod of parameter sharing\u003c\/li\u003e\n\u003cli\u003eMatrix multiplication and its importance\u003c\/li\u003e\n\u003cli\u003ePooling and dense layers\u003c\/li\u003e\n\u003cli\u003eIntroducing non-linearity relu activation function\u003c\/li\u003e\n\u003cli\u003eHow to train your convolutional neural network models using backpropagation\u003c\/li\u003e\n\u003cli\u003eHow and why to apply dropout\u003c\/li\u003e\n\u003cli\u003eCNN model training process\u003c\/li\u003e\n\u003cli\u003eHow to build a convolutional neural network\u003c\/li\u003e\n\u003cli\u003eGenerating predictions and calculating loss functions\u003c\/li\u003e\n\u003cli\u003eHow to train and evaluate your MNIST classifier\u003c\/li\u003e\n\u003cli\u003eHow to build a simple image classification CNN\u003c\/li\u003e\n\u003cli\u003eAnd much, much more!\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cstrong\u003eGet this book NOW and learn more about Convolutional Neural Networks in Python!\u003c\/strong\u003e\u003c\/p\u003e","brand":"Frank Millstein","offers":[{"title":"Default Title","offer_id":46537240117489,"sku":"2940163550531","price":3.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0674\/5433\/7265\/files\/2940163550531_p0.jpg?v=1765531661","url":"https:\/\/shop.barnesandnoble.com\/products\/2940163550531","provider":"Barnes \u0026 Noble","version":"1.0","type":"link"}