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Principles and Labs for Deep Learning

Principles and Labs for Deep Learning provides the knowledge and techniques needed to help readers design and develop deep learning;

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Deep Network Design for Medical Image Computing

principles of these tasks for deep learning approaches in medicine. These include skin disease classification, vertebrae identification and;

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Learn Keras for Deep Neural Networks

Extend deep learning principles into other popular frameworks Who This Book Is For Software engineers and data engineers with;

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Artificial Intelligence

, and Deep Learning in its many forms; key ML and DL algorithms data scientists should learn; ethical challenges for the use of AI; how AI;

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Labs on Chip

Labs on Chip: Principles, Design and Technology provides a complete reference for the complex field of labs on chip in biotechnology;

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Hands-On Deep Learning with Apache Spark

deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets;

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Deep Learning for Medical Image Analysis

Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This;

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PyTorch Deep Learning Hands-On

Hands-on projects cover all the key deep learning methods built step-by-step in PyTorch Key Features Internals and principles of PyTorch;

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R Deep Learning Essentials

Implement neural network models in R 3.5 using TensorFlow, Keras, and MXNet Key Features Use R 3.5 for building deep learning models for;

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Deep Learning from Scratch Building with Python from First Principles

With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many;

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Probabilistic Deep Learning

Probabilistic Deep Learning shows how probabilistic deep learning models gives readers the tools to identify and account for uncertainty;

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Hands-On Deep Learning Algorithms with Python

Understand basic to advanced deep learning algorithms, the mathematical principles behind them, and their practical applications. Key;

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Deep Learning in Computer Vision: Principles and Applications

where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and;

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Deep Learning and Convolutional Neural Networks for Medical Image Computing

This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation;

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Hardware Architectures for Deep Learning

, and IoT solutions. Efficient implementation of neural networks to support complex deep learning-based applications is a complex challenge for;

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50 More Stem Labs - Science Experiments for Kids

for your classroom, home, or homeschool needs. They support learning in these technical fields in a fun, hands-on, and sometimes competitive;

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CompTIA Network+ Study Guide with Online Labs

Virtual, hands-on learning labs allow you to apply your technical skills using live hardware and software hosted in the cloud. So Sybex has;

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Deep Learning and Convolutional Neural Networks for Medical Image Computing: Precision Medicine, High Performance and Large-Scale Datasets

This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation;

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Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D;

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Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D;

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Java Programming

learning tools and auto-graded coding labs for practicing and expanding your skills.;

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50 Stem Labs - Science Experiments for Kids

and up. Each one has a snappy title, a brief description of the task required, the rules, and grading rubrics. These are very adjustable for;

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Java Deep Learning Essentials

in and find out how to tackle Deep Learning Who This Book Is For This book is intended for data scientists and Java developers who want to;

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The Little Learner

accessible and fun Incremental approach constructs advanced concepts from first principles Presents key ideas of machine learning;

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Arnheim's Principles of Athletic Training

edition: Connect Athletic Training: the first online learning management system for the athletic training course, featuring assignable labs;

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Python Deep Learning

This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and;

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Deep Learning in Computer Vision

where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and;

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