Chevron Left
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
9,034 個評分
2,157 個審閱

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....

熱門審閱

BL

Oct 17, 2016

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

SZ

Dec 20, 2016

Great course!\n\nEmily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.

篩選依據:

226 - 机器学习基础:案例研究 的 250 個評論(共 2,077 個)

創建者 Santiago G

Jun 06, 2018

Useful introduction to machine learning.

創建者 Neha R

May 26, 2017

It's a really good course and covers all the basics extensively.

It is well structured and the case-study approach actually helps understanding the topics in a better manner and easily.

創建者 Junliang Z

Sep 22, 2017

My first course in Coursera! totally worth it

Good course to learn the basic theory about ML. Quiz and homework is instructive.

創建者 Stéphanie G

Jul 13, 2017

Amazing course, great structure for the first course of the specialization. Can't wait to start the second course!

創建者 Yue

Feb 24, 2018

Really great course

創建者 Veena J

Feb 25, 2018

Week 6 Quiz was confusing. Questions were ambiguous.

創建者 Mohammad S K

May 12, 2018

It was not easy for Novice like me. :)

創建者 Norman Y

Apr 25, 2018

Good beginning course. Week 6 could use more explanations and clearer examples. Somewhat difficult in the examples.

創建者 Romain V

May 27, 2018

loved the use case approach, very comprehensive and always easier using real life example as opposed to theoretical principles...

創建者 银大伟

Mar 24, 2018

this is a great course and I liked the way of teaching. Case studies are really helpful to understand the concepts behind the surface.

Thanks.

創建者 Deleted A

Apr 19, 2018

Well taught, info really sinks in. For python could we of used pandas.

創建者 Sabarish V

Apr 18, 2018

The course is easy to follow. With the IPython notebooks that are already filled in complementing the teaching, everyone can appreciate the applications of machine learning. What's even better is that, because of the notebooks, one can see that one doesn't necessarily need to be very skilled at maths or coding to build their own application.

創建者 Hitesh H

Jun 02, 2018

A very pragmatic approach. Complex concept were made simple to grasp and apply.

創建者 Manoj K B

May 27, 2018

Very good approach of learning, and the course material is designed very nice to get the gist of the class with an assignment

創建者 Suneel M

May 09, 2018

E

創建者 shikha a

May 06, 2018

Awesome!

創建者 rambarki g

Mar 11, 2018

This was a awesome moment for me it was really cool. The people of course era i love them .Thank you so much for financial aid. Keep supporting people like thank you thanks a lot!!!!

創建者 Tunuguntla S

Mar 28, 2018

very nice interaction

創建者 Neeraj S

Jun 08, 2018

I enjoyed the way the course was structured and examples provided

創建者 Vasudha S S

May 15, 2018

Excellent course to get started. Thanks you very much

創建者 Chi P H

Jan 23, 2018

The professors are very professional. They introduce this course by interesting way. Step by step from easy to hard. Strongly recommended.

創建者 何益帆

Feb 26, 2018

It is a perfect course about ML,especially for the students without much backgrounds.

創建者 Diego S L

May 13, 2018

It's a great course!

創建者 Rishab R

Apr 21, 2018

Very well presented and organised

創建者 Caio L F

May 24, 2018

Excellent course for those who wants to start to understand what really machine learning is. It goes beyond the theorical part, with pretty cool exercises. The case studies help us to visualize how the many applications we see at the real world work.