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

4.6
stars
9,235 ratings
2,202 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

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.

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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201 - 225 of 2,121 Reviews for Machine Learning Foundations: A Case Study Approach

By Carlos D M

Dec 21, 2015

Well-paced. Assignments are well executed. They are challenging enough to really force me to learn but not too easy that I'm feeling like I'm wasting my time.

This class in particular was somewhat high-level and left me very interested in the rest of the classes in the specialization.

By 张凌祺

Sep 29, 2015

A great course for beginners. Unlock the power of machine learning in a quite non - mathematical way. But even for people who are familiar with machine learning, you can learn some good pratical programming toolbox to help you prototyping or develop your machine learning application.

By Daniel S

Dec 12, 2015

I think this course is an excellent introductory survey of the topics and technologies relevant to machine learning. The teaching method is much more than a mere regurgitation of facts and contributes to an environment where topics can be truly learned and applied in the real world.

By Satish M G

Dec 09, 2016

This is an excellent course provided by the creators of this course. My sincere appreciation to both of them. The length of theory and practicals are very appropriate. I am very sure to continue all courses and finish them and master them. Thanks coursera for providing this course.

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 Saravanan C

May 26, 2017

The strategy of making people to become comfortable by first providing simple hands-on and building confidence is good. That will motivate them to stay along ALL the 6 course without getting perplexed. I see good team work! Thanks - I will strive to complete all the six modules.

By Ashar M

Oct 23, 2016

Great course, focused on practical learning and some of the widely used applications, such as sentiment analysis, product recommendations, image recognition etc. The videos are crisp and to the point and you will appreciate the amount of knowledge they pack in a very short time.

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 Alberto V

Jan 14, 2017

A very good introduction to foundations of machine learning. The learning methodology based on study cases is amazing and gripping and the ipython notebooks used in the practical sessions are very instructive. Strongly recommendable for everybody who want to start in this world

By Andre J

Mar 18, 2016

These Machine Learning classes have been fantastic so far, really enjoying them. Very good coverage of topics and challenging exercises to drive home the learning. The effort put into developing the classes has been superb and I look forward to the rest of the specialization.

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 Rohit G

Dec 11, 2015

I really loved the course ! It helped me greatly to gain an overall idea of the aspects of machine learning at the outset itself without confusing me with intricate details of the course and yet introducing to everything in there at a glance !

Really keeps you hungry for more !

By Maria Z

Oct 16, 2017

Great course, thank you very much! I had no previous experience with ML or programming, that was quite challenging for me to pass the assignment, but it was possible The material is being taught by the tutors very clear. I'm sure to continue my education with further courses.

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 Miguel A P L

Nov 28, 2016

Before taking this course I would not consider the topic as something that one could learn by himself.

The Course has opened my mind and has showed me that there is a lot to learn and study in order to fully master ML and AI in order to use it in the applications we can build.

By Gurunath M K

Sep 30, 2019

It was truly informative course. At the end of the course, I am sure I can say I know the all the key concepts behind Machine Learning. In near future, my focus will be be try to implement in relevant use-cases around. Thanks Accenture LKM and Coursera for facilitating this.

By Supriya N P K

Dec 09, 2015

Its a very basic course and a good start to learn Machine Learning.

Course was pretty easy to follow and the real world examples helped to visualize the applications of Machine Learning. Its highly recommended for the students who are completely new to the Machine Learning.

By Peter G

Feb 26, 2016

Very nice brief introduction into the field. Gives good overview of main concepts: 1) statements of problems in machine learning 2) approaches to finding solutions 3) methods to evaluate resulting solution . Systematic material presentation with good examples and analogies.

By Zachary N

Dec 13, 2015

Great overview of machine learning techniques and practices at a high level! There is sufficient material here to go from no machine learning knowledge (and a general programming background) to being able to create and deploy machine learning models for use in applications.

By Aman A

May 26, 2016

Awesome way of teaching that too from a well qualified faculty. Rather than imparting theoretical knowledge, great focus is on practical knowledge that's what I like about this Course. Thanks to Coursera for giving me this opportunity to get tutelage from such an erudite.

By Mayuresh W

Nov 23, 2015

The course was well detailed and gave a good idea of what to expect when learning about machine learning and this specialization.

Covering each of the topics well with sufficient explanation and a small project was a great way to learn.

Looking forward to the next courses :)

By Gerard Y

Jul 27, 2018

Very good overview, the lectures were enjoyable to follow, and brought good intuition on the topics with a good sense of what was possible. The exercises were of reasonable difficulty, and not too hard to set up, allowed to get a good feel of the potential of Turi Create.

By gaoyu_xinghuo

Jun 20, 2016

Exclude the last part, the whole session gave us the clear picture about machine learning -- What the machine learning is , how machine learning works and how to use machine learning to change the world:)

I love the course, it gave me a lot. Thanks Emily and Carlos again.

By Daniel R

Feb 07, 2016

It is a really well thought introduction for Machine Learning. It is almost unbelieveable that you could use every single technique in less than a month. Of course using a framework, but if you are really interested you could do them with open source tools.

It is amazing!

By alexandre l f

Oct 22, 2017

Case study base approach makes this course pragmatical and business oriented. A great team with good tools and exercise which deserves a 5.

Note : math's background is low (or more exactly far from the target of this course) and might be a blocking point at some stage.