Introduction to Machine Learning

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课程主页: https://www.coursera.org/archive/machine-learning-duke

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课程简介

Duke University

课程大纲

The focus of this module is to introduce the concepts of machine learning with as little mathematics as possible. We will introduce basic concepts in machine learning, including logistic regression, a simple but widely employed machine learning (ML) method. Also covered is multilayered perceptron (MLP), a fundamental neural network. The concept of deep learning is discussed, and also related to simpler models.

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课程详情

This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction. In addition, we have designed practice exercises that will give you hands-on experience implementing these data science models on data sets. These practice exercises will teach you how to implement machine learning algorithms with TensorFlow, open source libraries used by leading tech companies in the machine learning field (e.g., Google, NVIDIA, CocaCola, eBay, Snapchat, Uber and many more).

机器学习简介:本课程将为您提供机器学习模型(逻辑回归,多层感知器,卷积神经网络,自然语言处理等)的基础知识,并演示这些模型如何解决各种复杂问题。行业,从医学诊断到图像识别再到文本预测。此外,我们还设计了一些练习练习,这些练习练习将为您提供在数据集上实现这些数据科学模型的动手经验。这些实践练习将教您如何使用TensorFlow,机器学习领域领先技术公司使用的开源库(例如Google,NVIDIA,可口可乐,eBay,Snapchat,Uber等)实现机器学习算法。

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