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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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13,550 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

AH

Mar 27, 2022

very nice course.If you have basic knowledge of python datastructure then this course is best to start data science.All contents are beginner friendly which makes this course easily understandable.

RM

Feb 2, 2022

I was very disappointed with the exclusion of the final courses and the capstone project. The most interesting part of specialization no longer exists and no plausible justification has been given.

筛选依据：

1051 - Machine Learning Foundations: A Case Study Approach 的 1075 个评论（共 3,162 个）

创建者 Zakarie H

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Jul 8, 2017

I do really enjoyed it, the instructor knows the material and makes it fun to follow

创建者 Deleted A

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Nov 25, 2016

Excellent Course for those who want their fundamentals to be very clear and precise!

创建者 Dhruv T

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Jan 18, 2016

The teachers are very good. Makes the rest of the specialization even more exciting.

创建者 Zhihong C

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Oct 13, 2015

A very nice and effective approach. It makes the complicated problem easier to take!

创建者 Santhosh K J

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Jul 17, 2020

It was actually a good experience learning machine learning in this problematic way

创建者 Manali T

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May 27, 2020

Happy and satisfied with whatever I have learned and gain Knowledge in this course.

创建者 Ben D

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Oct 25, 2016

Very good overview of the type of thinking required to do Machine Learning on data.

创建者 Pujin W

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Oct 4, 2016

This course is fundamental to machine learning and helps me to grasp the idea of it

创建者 Yihong C

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Mar 27, 2016

a really interesting and efficient way to help students understand machine learning

创建者 Deleted A

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Dec 4, 2015

Excellent introdutory course. The only downside is the use of proprietary software.

创建者 Favian D

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May 28, 2020

This is the best online course I attended so far. It is easy to understand and fun

创建者 Amoghavarsha B

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Oct 28, 2019

Good course for ML beginners! Introduces us to the world of possibilities with ML.

创建者 Kaybee K

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Jan 24, 2017

As a totally new Jupytor learner, I've enjoyed this appetizer course fully enough.

创建者 Raymond D

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Dec 19, 2016

This Course really helped me to understand the basic concepts in Machine Learning.

创建者 Bill F

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Oct 1, 2016

Too much emphesis on graphlab. exercises should be prototyped and done in sklearn.

创建者 Bakhtawar U R

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Apr 4, 2016

A Great course. Professors are enthusiastic and well acknowledged about the topic.

创建者 王先生

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Jan 9, 2016

This Course is really a great way to get knowledge of the simple machine learning.

创建者 Alexander P

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Jul 21, 2021

Excelente que pasaran de Graphlab a Turicreate, dado que este ultimo es gratuito.

创建者 Kishore K

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Jul 12, 2020

The course was really interesting and drills into the basics of machine learning.

创建者 YASHKUMAR R T

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Mar 24, 2019

Best course to understand all the fundamentals of machine learning for beginners.

创建者 Arul T

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Sep 6, 2017

Excellent lessions to start with..Gifted to be part of these sessions.Very nice..

创建者 Andrey U

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Mar 10, 2016

Really great approach with a lot of useful and easy to get info. Really loved it!

创建者 Nickil M

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Nov 6, 2015

Enjoyed thoroughly.Nice way of implementing various tasks using ipython notebook.

创建者 Caleb B

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Dec 15, 2020

Great material and instruction. Very practical application as well. Well done!

创建者 Adel M

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Aug 29, 2020

this course is great for an introduction to ML, and the approach used is amazing