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

4.6
9,029 ratings
2,156 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

PM

Aug 19, 2019

The course was well designed and delivered by all the trainers with the help of case study and great examples.\n\nThe forums and discussions were really useful and helpful while doing the assignments.

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126 - 150 of 2,077 Reviews for Machine Learning Foundations: A Case Study Approach

By Jorge O

Apr 14, 2017

Easy to follow up. Very didactic!

Congratulations and thanks!

By Aruna H

Mar 16, 2016

Really like the case study approach. IPython notebook and graphlab are amazing tools. I am in week 4 now and was never bored. Hope the upcoming courses will be as good as this one.

By Khang V

Dec 31, 2015

Good course, interesting information and knowledge. I also love the exercises

By Ketan

Nov 07, 2016

Very good introduction course.

By Gerardo D O A

Aug 08, 2016

Great course, I like the practical approach!

By Patrick D

May 23, 2016

Love the structure for this course. Having a Case Study approach makes it easy to connect the abstract concepts and apply them to real worked use cases.

By Sourav D

May 08, 2016

Learnt many new concepts and is amazed by getting to know how machine learning is actually done.

By Lucas d L O

Aug 09, 2016

Great course for understanding introductory principles of the different areas of Machine Learning. The classes are very well taught and the exercises are very interesting. Highly recommended for beginners!

By Mahmoud A E

Feb 28, 2016

The top-down approach of this course is the best way to understand concepts and view solutions for real-world applications. This way I can go deeper after understanding why I am doing this.

By Erica B

Jun 05, 2016

This is a fantastic introductory course on Machine Learning, I really enjoyed working on it. The course has a great balance between theory and practice.

By AKASH S

Apr 11, 2016

This is course is great and the way its been taught by professors is very cool :)

I am getting to know the use case and than how we are going to do it, rather than conventional other way round. I am so happy that we first come to know about the application and its so important for a student to know that.

Thank you so much, only problem I see is that this course should have been started earlier :)

By mahmoud r

Mar 13, 2016

Best thing to get you into machine learning

By Sushil P B

Sep 08, 2016

A perfect kick start to your journey on Machine Learning!

By Awantik D

Feb 10, 2017

Perfect for getting started

By Varun R

Sep 23, 2017

The professors are really fun and the case study methodology to teach the concepts of machine learning was superb. !

By Saravana P

Dec 20, 2015

This course gave an introduction to ML concepts and applications. This course is good for absolute starters, as it doesn't scare the learner with hard core theoretical concepts. I learnt a fair bit about the overall ML scenario. Thanks to the instructors for making it fun to learn.

By Ramesh

Sep 21, 2016

Really good explanations of the topic with practical examples and implementations. Its like a quick recap of important concepts in ML. I would recommend this.

By Zachary C

Apr 30, 2017

A great primer on the various high level concepts in machine learning and some general applications as well as good quick intro to graphlab create. I was originally apprehensive to use another data science tool outside of panadas, but now think graphlab create is even better.

By Pavel K

Aug 05, 2016

A very clear and straightforward course giving a foundation for the following learning of Machine Learning.

By Haritz P

Mar 01, 2016

I really enjoyed this course. It's a very good introduction to Machine Learning. I already know a little bit of machine learning, R and Weka and I liked this course. I learned Machine Learning in Python and a little bit of NLP. I'm very excited to complete the specialization!!

By Omar M

Feb 28, 2016

Excellent course! I loved it! Good overview on machine learning

By Kyrylo S

Dec 28, 2015

Excellent presentation of material

By Iurii S

Oct 15, 2017

Great course! I like their approach of describing application first and then trying to use a fairly complete approach. Submissions in the form of quizzes and auto-graded assignments work better as one does not have to wait for other people to complete the course at the same time, which might be rare at the beginning and end of the session.

By Dheeraj A

Jan 03, 2017

Excellent Course.

By Bilkan E

Aug 18, 2016

Awesome course! Very helpful with a practical / example-driven approach that helps build intuition.