课程概述

In this course we will learn about Recommender Systems (which we will study for the Capstone project), and also look at deployment issues for data products. By the end of this course, you should be able to implement a working recommender system (e.g. to predict ratings, or generate lists of related products), and you should understand the tools and techniques required to deploy such a working system on real-world, large-scale datasets. This course is the final course in the Python Data Products for Predictive Analytics Specialization, building on the previous three courses (Basic Data Processing and Visualization, Design Thinking and Predictive Analytics for Data Products, and Meaningful Predictive Modeling). At each step in the specialization, you will gain hands-on experience in data manipulation and building your skills, eventually culminating in a capstone project encompassing all the concepts taught in the specialization....

学生对加州大学圣地亚哥分校提供的 Deploying Machine Learning Models 的评价和反馈

课程概述

1 - Deploying Machine Learning Models 的 7 个评论（共 7 个）

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热门在线专项课程

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Coursera

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学生对 加州大学圣地亚哥分校 提供的 Deploying Machine Learning Models 的评价和反馈

课程概述

1 - Deploying Machine Learning Models 的 7 个评论（共 7 个）

热门在线课程

热门在线专项课程

在线证书

在线学位课程

Coursera

社区

更多

学生对加州大学圣地亚哥分校提供的 Deploying Machine Learning Models 的评价和反馈