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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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13,532 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

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.

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.

筛选依据：

2626 - Machine Learning Foundations: A Case Study Approach 的 2650 个评论（共 3,157 个）

创建者 Clotilde D

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Jan 5, 2016

good overview, a little bit hard regarding the deep learning course, that would require more explanations

创建者 Hitesh D

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Oct 1, 2019

The course has helped me understand basic of Machine learning and has created interest for me.

Thanks :)

创建者 Pushpak T

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Mar 13, 2016

Gives a high-level understanding of machine learning concepts and focuses a lot on its application part.

创建者 Rajkumar D

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Mar 2, 2016

Good Start up with case study approach to just understand what we gonna learn in further specialization.

创建者 ashish

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May 2, 2018

The course from coursera was well delivered. Albeit, their seems to be too much dependency on graphlab.

创建者 Mohit A

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Nov 12, 2019

Great learning experience! We should have option of videos with exercises using Pandas & scikit learn.

创建者 Michele P

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Sep 4, 2017

Good introduction, although the implementation exercises use mainly GraphLab which is not open-source

创建者 Santosh W

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Feb 15, 2016

Useful course. Covered good amount of usecases for Machine learning concepts with handson experience.

创建者 Cristian C H M

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Jun 20, 2020

The videos are out dated and Turicreate doesn't work on Python 3.8 and the latest version of Ubuntu.

创建者 Jeff L

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Nov 29, 2015

This was a fantastic course for someone both unfamiliar with machine learning algorithms and python.

创建者 Tomáš Z

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Nov 30, 2018

Nice intro but it could have been more in depth, not just as a simple graphlab/turicreate tutorials

创建者 Jonathan E

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Aug 15, 2017

I liked the interactive python programming however the course could be more rigorous for my tastes.

创建者 Sergey G

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Mar 23, 2019

It'd be great to get rid of showing how teacher type code or write something, it's kind of boring.

创建者 DeepLyrics

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Dec 11, 2016

Great introductory course for beginners to machine learning and I loved the programming tutorials.

创建者 Alfonso M

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Mar 26, 2016

Instructors are clear and passional about their teaching. I wish the course was slightly deeper.

创建者 E. M S

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May 17, 2017

Good overview and programming warm-up. Just need to change the links to turi.com from dato.com

创建者 Laura M

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Feb 15, 2023

I would prefer the use of other tools better than turicreate , but the concepts are very clear

创建者 SANJEEV K V

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Mar 16, 2021

Nice Course and developed a nice understanding from the questions present in the assignments.

创建者 Tomas O

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Nov 8, 2019

It has a lot of problems with the programs you should install. But the content it's amazing.

创建者 MICHAEL G

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Nov 14, 2017

This course was a very good introduction to some of the techniques used in Machine Learning.

创建者 Stefan S

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Jan 4, 2016

Good intro to topics in machine learning as well as to Graphlab Create and iPython Notebook.

创建者 Stanislav B

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Apr 18, 2020

There were unnecessary problems with data. Last course (Clustering and retrieval is better)

创建者 weimin l

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Oct 27, 2016

A very interesting course! I learned a lot. Will continue on the next course once it ready.

创建者 Rishabh P

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Jul 26, 2020

It would be great if you start deployement of things in python also not only in turicreate

创建者 Brent R

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Jan 29, 2017

Good intro to ML, but would've enjoyed less of the "Black Box" approach in using Graphlab.