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Learner Reviews & Feedback for Machine Learning Foundations: A Case Study Approach by University of Washington

4.6
8,958 ratings
2,143 reviews

About the Course

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....

Top reviews

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.

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51 - 75 of 2,062 Reviews for Machine Learning Foundations: A Case Study Approach

By sravan

Oct 13, 2016

there is no proper documentation.

at least there should be some clear instructions for first program

By Xing W

Jul 03, 2016

I was expecting to solve problems using more open-sourced package. Unfortunately, I feel this series of courses are more of an advertisement for the instructor's software company.

By Valentin T

Jan 17, 2016

Using a proprietary library instead of widely used libraries and discouraging the use of open source widely used libraries. It barely compiles, the example notebook has method calls that use non existing methods of the SFrame object.

The course claims that it teaches the student how useful practical knowledge but then ends up using a non standard library and saying not to use pandas or scikit learn.

By Md R A

Dec 11, 2018

Great Experience

By Jungshen K

Dec 12, 2018

Very comprehensive and hand-on fashioned course, recommended!

By Satish K D

Nov 25, 2018

Very informative in basics of Machine Learning. It sets the stage for a deep dive into the topics of machine learning like Regression, Classification, Clustering etc.

By Myoungsu C

Nov 26, 2018

It was a great introduction!

By Md. R K

Dec 14, 2018

Awesome course to get started to ML with Python.

By Praveen B

Nov 28, 2018

The professors have taken it in a fun filled way. The material is also very interesting. This is an experience worth having.

By Sanjiban B

Nov 27, 2018

Great course. Thank you.

By 宁莽

Dec 15, 2018

以实际案例结合的讲解,非常有意义,对于新手来说,更能亲自体验到机器学习的强大

By Abhishek B

Dec 16, 2018

Good Machine Learning course for beginners.

By Praveen k

Dec 01, 2018

Good case studies to start with. Would have been better if python 3 was used. Please update and provide everything in python 3.

By Jithesh R

Nov 30, 2018

Great Experience...! Loved it...!

By AMAN M

Dec 18, 2018

I was totally new to the machine learning, but this course helped me to understand what is it? What is the importance of it ? where it can be used and what will be the future of it ? There was also enough exercise work to check our understanding to the topic learnt. I think it will be more interesting if they provide a console for code snippet for the assignment... It was very nice experience with Carlos Guestrin Sir and Emily Fox Ma'am

By Xue

Dec 02, 2018

Great course!

By Zohaib M

Dec 05, 2018

very good and excellent course.

By Shalini G

Dec 04, 2018

Nice course to understand the basics of Machine Learning

By Shakya S B

Dec 28, 2018

This course is very helpful for a beginner and provides a good foundation for the specialization and the advanced courses

By Yamin A

Dec 30, 2018

Excellent introductory course on Machine Learning. The material is taught at a level that does not require much in terms of pre-requisites, both in terms of the math and the programming requirements. From my perspective, I have an extensive background in Math, and some background in programming (MATLAB, R). I had not used Python prior to this course, and I found that I could keep up and learn both some Python and ML. I was able to finish the course in two weeks. Well done to the instructors who made the videos fun and accessible. Recommended for anyone who wants to learn something about ML.

By Jose E S S

Jan 13, 2019

Awesome, better course of machine learning.

By Lukasz W

Jan 01, 2019

Very good as an introduction to the further learning of ML

By Ezra S

Jan 01, 2019

The only way these courses could be better if there were far more of them from the same professors. If more of the nitty gritty details of these algorithms were fleshed out in all their glory, more algorithms, more mathematical derivations & more tutorials in the programming languages & libraries used. Otherwise, these MOOCs are near perfection. A very, very nice introduction for beginners with just a little bit of math & not too much programming. Just enough for busy people. I've reserved that 5th star due to the slow pace that the MOOCs have been released (which will presumably be irrelevant for future machine learners) & the fact that there really needs to be more of these very high quality moocs. So there aren't enough of them, so I reserve a star. Hopefully in the future that will be irrelevant as well in which case I'll regret not indicating 5 stars.

By Manu S

Jan 02, 2019

Excellent course. Explained all the ML concepts in detailed and easy way.

By OLZHAS S

Feb 16, 2019

Feeling still long way to go, at least took very serious track - with challenging assignments and re-learning required tasks!