返回到 Deploying Machine Learning Models
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
3.8
13 个评分
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.
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1 - Deploying Machine Learning Models 的 3 个评论（共 3 个）
创建者 Oriol P M
•Sep 18, 2019
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创建者 Arnaldo G d A e S
•Oct 03, 2019
This course is more about Reccommender Systems than deployment of models. Actually, there's just a few classes about model deployment, but no practical exercises. However, the Reccommender Systems classes are good for beginners. The teachers are good as well.
创建者 Murzakhmetov S
•Oct 24, 2019
Awful course, garbage content and no any peers to check your work
