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Deep Learning for Health Tech

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Deep Learning for Health Tech

Deep Learning for Health Tech
MP4 | Video: AVC 1920x1080 | Audio: AAC 48KHz 2ch | Duration: 1.5 Hours | 3.22 GB
Genre: eLearning | Language: English

Neural networks have been widely adopted across many industries as the ultimate pattern recognition tool. While their current uses in healthcare are limited, neural networks have a promising future in diagnostic and decision making applications, because of their ability to mimic—and improve on—human capabilities in health-related advice and treatment. This video explains the basics of neural networks; shows examples of training neural networks with both image-based and unstructured healthcare data; and describes the kinds of neural networks most likely to be useful for health-related applications. Examples are introduced using Python. Learners should have a basic understanding of Python, statistics, and machine learning (i.e., how training works and how to prepare data for training a model).

Survey a range of current neural network applications in healthcare using Python and TensorFlow
See examples of neural networks that underperform or get tricked in the health domain
Explore the promising future of using neural networks for pattern recognition problems in healthcare

Deep Learning for Health Tech

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  1. 健康科技与深度学习 神经网络已经为许多行业作为终极的模式识别技术所采用。但是在健康领域中的应用当前还比较有限,神经网络在诊断和决策制定应用方面有着光明的前景,这要归功于其模仿甚至改进人类在健康相关的意见和治疗方面的能力。本教程会讲到基础的神经网络知识;演示使用基于图像和非结构化数据训练神经网络的案例;以及描述与健康应用相关的最有用的神经网络应用。所用到的案例是基于Python的。学习者应掌握基本的Python、统计学以及机器学习知识。 主要内容: • 了解当前神经网络在健康领域使用Python和Tensorflow的应用 • 分析神经网络在健康领域表现不佳的情况 了解使用神经网络用于健康领域中模式识别问题的前景
    wilde(特殊组-翻译)11个月前 (11-15)