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返回到 Machine Learning Foundations: A Case Study Approach

学生对 University of Washington 提供的 Machine Learning Foundations: A Case Study Approach 的评价和反馈

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13,543 个评分

课程概述

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....

热门审阅

RH

Jun 8, 2017

I felt this course did a good job introducing the student to Machine Learning. The examples and hands on assignments brought the concepts home. I was able to use the knowledge immediately at work.

SS

May 18, 2020

The course was very informative but I face a lot of problems in installing Graphlab and Turicreate. I request the Mentors please use the Pandas data frame in place of SFrame. The mentors are cool.

筛选依据：

926 - Machine Learning Foundations: A Case Study Approach 的 950 个评论（共 3,159 个）

创建者 Omar N T

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Mar 30, 2016

All thanks to Carlos and Emily.

This course is great for knowing what ML is with practical examples :)

创建者 Sowrabh N R S

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Nov 19, 2015

Great course.

Focuses on the fundamentals and the practice part more. It helps you get a flair for ML.

创建者 Tavva S T

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Jun 7, 2020

I'll be very thankful to the team of coursera. A single sentence - " You guys are really AMAZING!! "

创建者 Joshua T (

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Apr 30, 2020

Excellent Course! Very easy for a total beginner to understand and I feel like I have learned a lot!

创建者 Subhradeep B

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Jun 18, 2017

Nice course for beginners. Helped me a lot to get an insight of complex concepts like deep learning.

创建者 Chris L

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Dec 3, 2016

Lots of fun, and a great introduction to ML. Will definitely be continuing on in the specialization

创建者 Zeyu K

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Aug 15, 2016

Wonderful! Both material and teachers are very interesting. Can't wait to continue their next class.

创建者 David E

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Mar 3, 2016

A remarkable introduction to key approaches to Machine Learning. I'm excited for the coming courses!

创建者 Dominic C

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Feb 7, 2016

Very well designed, the setting up the environment was well documented, with alternative approaches.

创建者 Sunny P T

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Jan 2, 2016

This course is awesome. Teaching style of intructor is amazing . Thanks for such a wonderful course.

创建者 Da-Rin Q

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Oct 30, 2015

A great course if you want to learn some basics in machine learning and where/how it can be applied.

创建者 Sadat B F

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May 3, 2020

I really enjoyed the course . Have learnt a lot of fundamentals of ML and Really helpful for futute

创建者 Kowshiha P

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Dec 28, 2016

Very well taught, concepts clearly explained, a good introduction to the world of machine learning!

创建者 Li D

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Dec 26, 2016

This course is quite advanced. You should do this after you have finished the one from Stanford U.

创建者 Bilkan E

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Aug 17, 2016

Awesome course! Very helpful with a practical / example-driven approach that helps build intuition.

创建者 mithun g

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Jan 28, 2016

A very nice approach to learning Machine Learning. Doesn't scare you with lot of technical jargons.

创建者 Wenqi Z

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Jan 16, 2016

The programming assignment really put the learning into practice. It's very practical and hands on.

创建者 Zhubin W

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Jan 9, 2016

这门课是系列课程的第一门，比较基础，我是在上完Andrew的Machine Learning课程后上的， 通过这门课程，开始逐渐习惯了利用Python语言处理相关模型的方法,我会继续跟进系列课程的。

创建者 Vinay S

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Jul 6, 2020

Too awesome course i really enjoy it, teaching way was too good,and teacher also. Thanku Coursera!

创建者 kamrun n

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May 4, 2020

I had BEST learning experience in this course. It is very easy to understand and to implement too.

创建者 Almir I

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Mar 5, 2019

Great course. Very clear and detailed presentation of concepts and techniques of Machine Learning.

创建者 Bigyan S

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Nov 18, 2017

Just what I needed. Goes through the applications first and then to the theoretical aspects later.

创建者 Asif K

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Nov 16, 2016

Good course to build concepts of machine learning that is good platform to move to advanced level.

创建者 Zhiming L

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Oct 14, 2015

The course is very basic, and I learned a lot how to write Python code and using the GraphLab tool

创建者 Harshit G

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Aug 11, 2020

Condensed and rich information delivered through informative videos and useful jupyter notebooks.