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Introduction to Deep Learning Business Applications for Developers

Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples;

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Deep Learning: Algorithms and Applications

This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent;

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Deep Learning for Hydrometeorology and Environmental Science

This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution;

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Deep Learning for Hydrometeorology and Environmental Science

This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution;

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Deep Learning in Data Analytics

This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various;

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Deep Learning on Edge Computing Devices

Deep Learning on Edge Computing Devices: Design Challenges of Algorithm and Architecture focuses on hardware architecture and embedded deep;

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Trends in Deep Learning Methodologies

Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep;

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Advanced Deep Learning Applications in Big Data Analytics

in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a;

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Deep Learning Applications

This book presents a compilation of selected papers from the 17th IEEE International Conference on Machine Learning and Applications (IEEE;

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Deep Learning

This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent;

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Multimodal Scene Understanding

Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a;

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Emerging Deep Learning Applications of Short Range Radars

This exciting new resource presents emerging applications of artificial intelligence and deep learning in short-range radar. The book;

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Deep Learning Applications Volume 2

This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It;

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Examining the Impact of Deep Learning and IoT on Multi-Industry Applications

efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and;

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Deep Neural Networks and Applications

. Also discussed in the book is the optimization of deep learning for the best performance of e-learning data, the methodology and the research;

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Hands-On Deep Learning with R

Explore and implement deep learning to solve various real-world problems using modern R libraries such as TensorFlow, MXNet, H2O, and;

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TensorFlow 2 Reinforcement Learning Cookbook

Features Develop and deploy deep reinforcement learning-based solutions to production pipelines, products, and services Explore popular;

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Deep Learning for Coders with fastai &

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates;

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Deep Learning with Applications Using Python

Explore deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and;

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Deep Learning for Data Analytics

Deep learning, a branch of Artificial Intelligence and machine learning, has led to new approaches to solving problems in a variety;

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Handbook of Research on Applications and Implementations of Machine Learning Techniques

it's detecting disease or generating algorithms, deep learning techniques are advancing exponentially. Researchers and professionals need a;

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Handbook of Deep Learning Applications

processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning;

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Python Reinforcement Learning Projects

Implement state-of-the-art deep reinforcement learning algorithms using Python and its powerful libraries Key Features Implement Q-learning;

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Deep Learning and IoT in Healthcare Systems

This new volume discusses the applications and challenges of deep learning and the internet of things for applications in healthcare. It;

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Data-Driven Evolutionary Optimization

Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning;

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Deep Learning

learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and;

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Advanced Deep Learning with R

Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R libraries Key;

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