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

4.6
9,047 ratings
2,162 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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76 - 100 of 2,081 Reviews for Machine Learning Foundations: A Case Study Approach

By Hritik K S

Feb 25, 2019

I learned the understanding that how we approach Machine Learning models.

By Aldo V M

Feb 25, 2019

Excellent course Carlos & Emily! I enjoyed your lectures a lot, ML is complex but you guys found the way to deliver the message clear, easy and in a funny way. Using real world examples was amazing. Guys could you let me know which other courses you are teaching? Ill be glad to continue learning from you guys. Many thanks, obrigado amigos.

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!

By Chandan K M

Feb 27, 2019

well crafted course.

By Ganesh K

Feb 10, 2019

Learning things with good use cases always lot better. This course really helped a lot to understand machine learning clearly. Throughout this course the explanation of the concepts are so clear and assessments are so intuitive.

By Erick V

Mar 02, 2019

Excelente curso, te da una visión general de todo lo que puedes hacer en ML

By Chao L

Mar 04, 2019

It is good class for people want to ML and start from scratch

By sohan l b

Mar 04, 2019

This course is good for beginners.This course covers hands-on as well as Basic theory and their applications .

By Mohit C

Mar 05, 2019

The idea on the teaching method by taking case study was a great choice. Great work keep it up.

By Aries F

Mar 06, 2019

Very easy to understand, code are very simple and to the point

By Lahiru H P

Mar 04, 2019

great course content to get started with machine learning and also for deep learning.

By Almir I

Mar 05, 2019

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

By Akash G

Mar 08, 2019

START basic like star

By Evan S

Mar 11, 2019

This course was a great balance between lecture (and lecture quiz) & iPython lecture (and iPython lecture quiz). I like that the answers are multiple choice as opposed to copying and pasting code. That way, any coding errors can be played around with in the notebook first without using up any submission attempts. Emily and Carlos did a great job of keeping the course fun while sticking to the easy-to-understand case-study approach.

By Abbas S

Mar 01, 2019

wonderful learning experience

By Sharad J

Mar 23, 2019

The ML concept is explained with use cases and demonstrated with python programs which

By Arif A

Mar 25, 2019

I have a fairly good background in mathematics and have read through major parts of the Deep Learning Textbook by Goodfellow et. al. One year later I wanted to revise ML again. People who are complaining that there is no mathematical or algorithmic rigor in this course need to understand that this is meant to be an introductory course in order to pique interest in the learner and drive him/her to pursue this field further. Heavy focus on math and algorithms straightaway does not work for most people. Hence, I conclude that this is a good intro course which does it's job quite well.

By YASHKUMAR R T

Mar 24, 2019

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

By CHIRANJI L C

Mar 28, 2019

practical exposure is excellent!

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 Muhammad A N

Dec 06, 2018

Excellent

By Christopher M

Dec 07, 2018

This was a great course. The instructors were fun and knowledgeable and the assignments were well-written. I loved the flexibility of being allowed to use whatever software I wanted to solve the ML assignments since the quizzes were based on the results of the modeling rather than submitted code. For some assignments I used sklearn and for others I used the software recommended by the instructors (graphlab).

By Divyansh S

Dec 25, 2018

I found this course advantageous for me. I found the case study approach of teaching the various concepts of Machine Learning quite helpful. Case Study approach gives us the idea of practical implementaton of these concepts in real life. The quality of the teaching content was very good. Moreover the assignments helped a lot in understanding some of the key concepts. Ideal course for newbies to start learning Machine Learning.

By Md R A

Dec 11, 2018

Great Experience