| 期刊全稱 | Advanced Applied Deep Learning | | 期刊簡稱 | Convolutional Neural | | 影響因子2023 | Umberto Michelucci | | 視頻video | http://file.papertrans.cn/146/145243/145243.mp4 | | 發(fā)行地址 | The first book with extensive examples of advanced deep learning techniques including CNN.Uses real-life datasets in the application of advanced techniques.Guides you from easier examples to more adva | | 圖書封面 |  | | 影響因子 | .Develop and optimize deep learning models with advanced architectures. This book teaches you the intricate details and subtleties of the algorithms that are at the core of convolutional neural networks. In .Advanced Applied Deep Learning., you will study advanced topics on CNN and object detection using Keras and TensorFlow.?.Along the way, you will look at the fundamental operations in CNN, such as convolution and pooling, and then look at more advanced architectures such as inception networks, resnets, and many more. While the book discusses theoretical topics, you will discover how to work efficiently with Keras with many tricks and tips, including how to customize logging in Keras with custom callback classes, what is eager execution, and how to use it in your models. .Finally, you will study how object detection works, and build a complete implementation of the YOLO (you only look once) algorithm in Keras and TensorFlow. By the end of the book you will have implemented various models in Keras and learned many advanced tricks that will bring your skills to the next level..What You Will Learn..See how convolutional neural networks and object detection work.Save weights and mode | | Pindex | Book 2019 |
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