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返回到 机器学习基础:案例研究

學生對 华盛顿大学 提供的 机器学习基础:案例研究 的評價和反饋

4.6
12,351 個評分
2,960 條評論

課程概述

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies. At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images. Through hands-on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains. This first course treats the machine learning method as a black box. Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output. In subsequent courses, you will delve into the components of this black box by examining models and algorithms. Together, these pieces form the machine learning pipeline, which you will use in developing intelligent applications. Learning Outcomes: By the end of this course, you will be able to: -Identify potential applications of machine learning in practice. -Describe the core differences in analyses enabled by regression, classification, and clustering. -Select the appropriate machine learning task for a potential application. -Apply regression, classification, clustering, retrieval, recommender systems, and deep learning. -Represent your data as features to serve as input to machine learning models. -Assess the model quality in terms of relevant error metrics for each task. -Utilize a dataset to fit a model to analyze new data. -Build an end-to-end application that uses machine learning at its core. -Implement these techniques in Python....

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PM
2019年8月18日

The course was well designed and delivered by all the trainers with the help of case study and great examples.\n\nThe forums and discussions were really useful and helpful while doing the assignments.

BL
2016年10月16日

Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much

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2601 - 机器学习基础:案例研究 的 2625 個評論(共 2,870 個)

創建者 Waquar R

2016年8月8日

this is really good

創建者 Vivek A

2016年4月18日

Enjoyed this class.

創建者 Fei F

2015年12月22日

Easy for beginners.

創建者 Explore I

2019年11月15日

Awesome Experience

創建者 Binil K

2016年1月10日

Really great one!!

創建者 Quang H N

2015年12月28日

Good for ML newbie

創建者 amit d

2020年2月3日

nice explaination

創建者 ARNAB N

2020年1月5日

Very nice program

創建者 Rahul S

2020年12月19日

GREAT EXPERIANCE

創建者 SURUTHI T

2020年7月5日

more informative

創建者 Oscar M

2016年5月29日

Very insightfull

創建者 Tulasi P D

2020年7月15日

it is so useful

創建者 Rohith m

2020年4月17日

very intersting

創建者 shane

2015年10月22日

Very practical.

創建者 Rohit K S

2020年9月30日

Good Course!!

創建者 Divyashree

2020年9月14日

A good course

創建者 Rupali G

2017年11月2日

good content

創建者 André G

2016年5月14日

Good course.

創建者 廖敏宏

2020年9月24日

Very useful

創建者 P.BHUVANASHREE

2020年9月18日

interesting

創建者 HASNA V N

2020年7月19日

Good course

創建者 Shubham D

2016年12月3日

nice course

創建者 Le H P

2019年8月16日

well done!

創建者 Daniel Ø

2016年1月18日

very basic

創建者 Muhammad A K

2020年11月27日

very good