Advanced Deep Learning with Python

Description: Advanced Deep Learning with Python [Paperback] Vasilev, Ivan Product Overview Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystemKey FeaturesGet to grips with building faster and more robust deep learning architectures Investigate and train convolutional neural network (CNN) models with GPU-accelerated libraries such as TensorFlow and PyTorch Apply deep neural networks (DNNs) to computer vision problems, NLP, and GANsBook DescriptionIn order to build robust deep learning systems, you'll need to understand everything from how neural networks work to training CNN models. In this book, you'll discover newly developed deep learning models, methodologies used in the domain, and their implementation based on areas of application. You'll start by understanding the building blocks and the math behind neural networks, and then move on to CNNs and their advanced applications in computer vision. You'll also learn to apply the most popular CNN architectures in object detection and image segmentation. Further on, you'll focus on variational autoencoders and GANs. You'll then use neural networks to extract sophisticated vector representations of words, before going on to cover various types of recurrent networks, such as LSTM and GRU. You'll even explore the attention mechanism to process sequential data without the help of recurrent neural networks (RNNs). Later, you'll use graph neural networks for processing structured data, along with covering meta-learning, which allows you to train neural networks with fewer training samples. Finally, you'll understand how to apply deep learning to autonomous vehicles. By the end of this book, you'll have mastered key deep learning concepts and the different applications of deep learning models in the real world.What you will learnCover advanced and state-of-the-art neural network architectures Understand the theory and math behind neural networks Train DNNs and apply them to modern deep learning problems Use CNNs for object detection and image segmentation Implement generative adversarial networks (GANs) and variational autoencoders to generate new images Solve natural language processing (NLP) tasks, such as machine translation, using sequence-to-sequence models Understand DL techniques, such as meta-learning and graph neural networksWho this book is forThis book is for data scientists, deep learning engineers and researchers, and AI developers who want to further their knowledge of deep learning and build innovative and unique deep learning projects. Anyone looking to get to grips with advanced use cases and methodologies adopted in the deep learning domain using real-world examples will also find this book useful. Basic understanding of deep learning concepts and working knowledge of the Python programming language is assumed.Table of ContentsThe Nuts and Bolts of Neural NetworksUnderstanding Convolutional NetworksAdvanced Convolutional NetworksObject Detection and Image SegmentationGenerative ModelsLanguage ModellingUnderstanding Recurrent NetworksSequence-to-Sequence Models and AttentionEmerging Neural Network DesignsMeta LearningDeep Learning for Autonomous Vehicles Read more Details Publisher ‏ : ‎ Packt Publishing (December 12, 2019) Language ‏ : ‎ English Paperback ‏ : ‎ 468 pages ISBN-10 ‏ : ‎ 178995617X ISBN-13 ‏ : ‎ 77 Item Weight ‏ : ‎ 1.78 pounds Dimensions ‏ : ‎ 9.25 x 7.52 x 0.97 inches Best Sellers Rank: #1,287,756 in Books (See Top 100 in Books) #252 in Computer Vision & Pattern Recognition #492 in Computer Neural Networks #1,386 in Python Programming #252 in Computer Vision & Pattern Recognition Quality Products This will be shipped securely Returns must be within 30 days - item EXACTLY as it was sent. Must have tracking number. Email us with any issues/questions. Thanks for looking! Fast and Free Shipping Shipping is free for this item. We get your order shipped out and delivered to your doorstep as quickly as possible. Commitment We are committed to making sure that you leave this transaction satisfied. That means having access to real people that get your questions and concerns answered quickly. Give us a shot and we will make sure that you will look to us again!

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