Learning Deep Learning: Theory and Practice of Neural Networks, Computer Vision, NLP, and Transformers using TensorFlow by Magnus Ekman
Requirements: .ePUB reader, 43 mb
Overview: Deep learning (DL) is a key component of today’s exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others–including those with no prior machine learning or statistics experience.
After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers, Magnus Ekman shows how to use them to build advanced architectures, including the Transformer. He describes how these concepts are used to build modern networks for computer vision and natural language processing (NLP), including Mask R-CNN, GPT, and BERT. And he explains how a natural language translator and a system generating natural language descriptions of images.
Genre: Non-Fiction > Tech & Devices
Download Instructions:
Learning_Deep_Learning_Theory_and_Practice.epub
Learning_Deep_Learning_Theory_and_Practice.epub
