Machine Learning: Classification

开始时间: 01/18/2020 持续时间: Unknown

所在平台: Coursera

课程类别: 计算机科学

大学或机构: CourseraNew



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第一个写评论        关注课程


Classification is one of the most widely used techniques in machine learning, with a broad array of applications, including sentiment analysis, ad targeting, spam detection, risk assessment, medical diagnosis and image classification. The core goal of classification is to predict a category or class y from some inputs x. Through this course, you will become familiar with the fundamental models and algorithms used in classification, as well as a number of core machine learning concepts. Rather than covering all aspects of classification, you will focus on a few core techniques, which are widely used in the real-world to get state-of-the-art performance. By following our hands-on approach, you will implement your own algorithms on multiple real-world tasks, and deeply grasp the core techniques needed to be successful with these approaches in practice. This introduction to the course provides you with an overview of the topics we will cover and the background knowledge and resources we assume you have.





这门课程关注机器学习里面的另一个基本问题: 分类(Classification), 通过两个案例研究进行学习:情感分析和贷款违约预测,最终通过Python实现相关的算法(也可以选择其他语言,但是强烈推荐Python)。 Case Studies: Analyzing Sentiment & Loan Default Prediction


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