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

4.6
9,110 ratings
2,175 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

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.

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

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51 - 75 of 2,093 Reviews for Machine Learning Foundations: A Case Study Approach

By Ken C

Feb 04, 2017

Not happy about course 5 & 6 got cancelled.

By Shane C

Nov 16, 2016

I did not find the course very good. I came into the class with only real basic knowledge of Python and I was hoping to be able to pick up more as part of this class. WHile I might have picked up more, it was only because I used resources outside the course.

The video instructions in programming in Python left quite a few gaps to figure out by reading documentation. The videos themselves were divided into two sections -- first a theoretical or classroom like section and a second a lab/programming section going over some coding in Python. The 'classroom' type lectures were pretty reasonably good. But the lab/programming were pretty terrible.

They instructor really break down the syntax of the code and just left the student to figure it out. This made being able to take this code and to adapt it to other uses very difficult.

I would not recommend this as a course to help learn Python.

By Dmitri K

May 27, 2016

The whole course based on some proprietary software. In general, it seems that the main goal of the course is promote that software.

By Yaron K

Jul 13, 2016

The Lecturers are very enthusiastic, but I was hoping for examples and assignments based on Pandas and Skikit-Learn. Instead the course examples and assignments are based on a machine learning package called Graphlab, that stopped working when it was upgraded to version 2 (there are workarounds that enable it to work locally, but clearly it isn't "enterprise ready")

By Mario L

Nov 24, 2015

I dont like the tools they used, it seems like a promotion for their company.

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 Sameh

Jan 20, 2019

very good and very nice course, it added lots to me

By Genyu Z

Jan 20, 2019

This course is very useful. Firstly, it helps me to build a perfect python environment. Secondly, it teaches me how to use jupyter notebook correctly. Teachers are very kind, and I like their teaching ways. If I can build algorithm without graphlab, it will be more challenging.

By Aleksander S

Feb 01, 2019

This is a great course. The content is delivered at a very good pace even for people with little prior knowledge of statistics or computer science — not too fast (would be too difficult) and not too slow (could become boring). Additionally, the assignment model is perfect — it requires completing hands-on exercises, but then the solution is assessed using simple quizzes. Thanks to that the answers and the grades are immediately available.

By DIVYANSH S

Feb 03, 2019

EXCELLENT

By Jonathan K

Jan 22, 2019

Very nice, will continue with the rest of the specialisation

By Walt M

Feb 04, 2019

create videos and hands on practices

Neural network part should be enhanced with more common frameworks, such as TensorFlow/Keras

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 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 Md. R K

Dec 14, 2018

Awesome course to get started to ML with Python.

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 Manu S

Jan 02, 2019

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

By Lukasz W

Jan 01, 2019

Very good as an introduction to the further learning of ML

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 Rania B

Jan 06, 2019

I had to use TuriCreate instead of GraphLab, so other than the changes in the libraries that had me guessing which function to use, everything in this course is well structured and concrete. Thank you all!

By Artem

Jan 08, 2019

awesome course with theoretical and practical knowledge

By Madan R

Feb 12, 2019

Good course, It give motivation for people to learn ML.

By Amogh B

Feb 22, 2019

Its really wonderful course to get the familiarise with the basics of Machine Learning

By Rohan V

Feb 13, 2019

this has been one of the best courses that I have taken online and the output from this is seriously amazing. It really makes your brain work and the forums make sure you don't get lost. I am definitely going to do the specialization course