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Deploying Machine Learning Models(으)로 돌아가기

캘리포니아 샌디에고 대학교의 Deploying Machine Learning Models 학습자 리뷰 및 피드백

28개의 평가
8개의 리뷰

강좌 소개

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....
필터링 기준:

Deploying Machine Learning Models의 7개 리뷰 중 1~7

교육 기관: 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.

교육 기관: Oriol P M

Sep 18, 2019


교육 기관: shaikh i

Jul 01, 2020

The course was really good. I thought it is related with flask or django, but only introduction was given and they didn't teach flask. The name of the course should be "building recommendation systems" in my opinion.

교육 기관: cherif g

May 28, 2020

It was not what I expected. Sorry my mistake

교육 기관: Eduardo A C

Apr 14, 2020

Eu achei um pouco superficial.

교육 기관: Mansi P

May 15, 2020

Deployment was not even taught. misleading title, underwhelming content.

교육 기관: Murzakhmetov S

Oct 24, 2019

Awful course, garbage content and no any peers to check your work