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code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors;
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a hands-on experience with speech processing, in particular speech coding. Born out of the need for laboratory materials for the Digital;
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Help for grown-ups new to coding Getting a jump on learning how coding makes technology work is essential to prepare kids for the;
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This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time;
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fast, efficient, and accurate deep learning tasks. Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations;
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solved by supervised learning algorithms with deep neural networks. You'll tackle one use case for regression and another for classification;
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learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with;
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Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals;
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help you understand popular deep learning architectures and their variants in R, along with providing real-life examples for them. This deep;
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efficient deep learning models, Hands-On Deep Learning with Apache Spark is for you. Knowledge of the core machine learning concepts and some;
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, including its implications for civic life and the economy, and unpacks the surprising history of the field, beginning with the first coders;
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, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding;
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Take a deep dive into deep learning Deep learning provides the means for discerning patterns in the data that drive online business;
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performance of your models For readers with an intermediate knowledge of Python, Jupyter notebooks, and machine learning.;
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helpful tips and best practices for making the most of the framework. Next, yoĆ¼ll learn how to train models effectively with transfer learning and;
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and Challenges provides readers with a focused approach for the design and implementation of deep learning concepts using data analytics;
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? Whether you are familiar with machine learning or are new to this domain, The Deep Learning Workshop will make it easy for you to understand deep;
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other previously impossible applications. Deep Learning with R is for developers and data scientists with some R experience who;
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Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition;
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Dive into the future of data science and learn how to build the sophisticated algorithms that are fundamental to deep learning and AI with;
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Build, implement and scale distributed deep learning models for large-scale datasets About This Book * Get to grips with the deep;
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real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific;
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real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific;
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Learn how to solve challenging machine learning problems with TensorFlow, Google's revolutionary new software library for deep learning. If;
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Explore the world of neural networks by building powerful deep learning models using the R ecosystem Key Features Get to grips with the;
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in deep learning with digital technology. It also serves as an excellent resource for researchers and individual professionals who seek to;
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collaboration, deep learning visualization, and data preparation for deep learning. To help clarify the complex topics discussed, this book includes;
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