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

4.6
stars
12,194 ratings
2,917 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 18, 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 16, 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 2,827 Reviews for Machine Learning Foundations: A Case Study Approach

By Theodore G

Oct 23, 2016

A really interesting, introductory course in Machine Learning Methods and their applications. The case study approach followed by the instructors makes it ideal to learn how these ideas used in real-life problems. The programming language used is Python (GraphLab Create or Open Sourced libraries), which is most probably the best choice for newcomers in the field.

By Fabio P

Mar 25, 2016

After going on with the specialization I started to understand how great this first course really was: It teaches you lots of basics while not expecting too much and shows how you can use machine learning in different scenarios.

On it's own it's possibly only worth 3 stars, but in the context of the whole specialization and further courses it's definitely 5 stars!

By Paul P

Mar 7, 2017

This course is great for anyone who wants to not only get a great overview of the concepts of machine learning but apply the concepts and see the results in week 1! You'll be using machine learning algorithms to train models with real data even if you have no idea what that means! If you're taking the time to read this review you should probably take the course!

By Matthew B

Jun 4, 2016

This is a great class! Highly recommended. Emily and Carlos are a great team. The videos are polished, the progression through the material is well organized and everything just fits together very well in this specialization. The assignments are challenging enough to be worth the effort. Great specialization... I look forward to completing every class.

By Stefan K

Dec 28, 2015

Very good introduction to machine learning, the teachers and assignments are very well planned and executed. It is a course where you can spend more time, as the workload is bigger than at usual courses, but you learn a lot every week. I am really fan of this Specialization and I plan to complete the whole Specialization given enough time in near future.

By YASEEN S Z

Oct 7, 2017

You were very near to be the legend of Machine Learning but after cancelling the capstone project you aren't. I'm really disappointed, why great things always not completing. I wish you to provide us with at least IPYNB for the capstone project because that will help us a lot. Finally, this is a really amazing course. Thank you for this great course.

By 이제민

Dec 13, 2015

that's awesome course. They bridged between theorem and practice. so we can imagine and know how to apply machine learning algorithm in real world and real problem. what's more, we can adjust and tuning machine learning algorithm to make customized algorithm. I am very confidence this course should give everyone great opportunities and good insight.

By Suchismita R

Sep 14, 2019

Machine Learning Foundations manages to provide a very intuitive impact on the understanding of the need and the accuracy of various ML techniques. The course takes the participant through a thorough conceptual and program-based approach. The various Algorithms and concepts are explained in utmost details, and the exercises are fun and challenging.

By AMS - o

Jul 22, 2019

Aside from few technical difficulties, a very well designed and thorough course - this case-study approach is obviously a lot more involving and relatable than just dragging one through a bunch of theoretical concepts and equations (not that the latter is inherently bad, the other one is just more fun :). Would recommend to anyone interested in ML.

By Omar S

Aug 22, 2016

A Brilliant introduction to Machine Learning, I've tried several courses before but none of them got me engaged like this one. The instructors have a lot of knowledge and present the material in a very easy to understand way. Also the assignments and technical work is really engaging and challenges you to really learn the language and the concepts.

By A. B

Feb 29, 2016

Great course--I love the case study approach! Combined with both instructors enthusiasm for the subject, the approach was a great way to ground the theory. The quizzes & labs guided a deeper exploration into the topics the details presented in the modules.

I'm excited to continue digging into the course material while moving towards the capstone.

By Daniyar M

Feb 17, 2016

I thoroughly enjoyed the course. I was hearing about Machine Learning so much that i decided to see whats the big buzz about, and big it was! Now i have some of the ideas for my own projects and some solutions for old problems. And must i say that the instructors are amazing, really love their job! Will definitely use graphlab in my work from now.

By Teo J

May 8, 2020

First of all, I want to say that the interactions between the two professors was, in the most academically professional way, adorable. They clearly know and love their material, and are clearly relaxed and enjoying teaching. It was easy to learn from them, the lessons were well-scaffolded, and I only wish I could take courses like this on campus.

By Sabarish V

Apr 18, 2018

The course is easy to follow. With the IPython notebooks that are already filled in complementing the teaching, everyone can appreciate the applications of machine learning. What's even better is that, because of the notebooks, one can see that one doesn't necessarily need to be very skilled at maths or coding to build their own application.

By Hans G Q

Oct 11, 2020

An amazing course! If you don't have any idea of what is Machine Learning, you will find this course very helpfull. You will walk through different mathemathical concepts as well, but with some research you will doing well!. Excellent for have a big picture of what's going on with Machine Learning and see practical examples on how it works!

By v s

Mar 24, 2018

this is pretty cool, I enjoy this course and the dynamic between the instructors. This course touched on important concepts and purposely omitted the details of the underlying math and algorithm in order to give you a bird-eye-view of the ML landscape. It also wets my appetite to learn more about the details behind the magic! Good approach.

By Alan L

Dec 21, 2017

Amazing Introduction to ML. I came in with little understanding of ML and no Python or coding experience. I had to do most weeks twice while learning extra Python on the side from Code Academy but if a complete novice like me can do this anyone can! The professors are great- they're great at breaking down complex ideas into simple examples.

By Bruno L

Dec 19, 2016

In this course, you use ML algorithms that are already implemented to solve various kinds of problems. The goal is to give you a broad overview of ML and how it can be used to solve real life problems.

Subsequent courses of this specialization dive deeper in each algorithm. You'll learn the theory behind them and implement them from scratch.

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 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 Nelson P

Oct 30, 2017

Great introductory course to ML! I learned some valuable insights by building actual models using GraphLab. After taking this course, you'll have the foundations and overview of machine learning to take the follow up courses in the ML certification by same instructors or take any other ML course available out there. Highly recommended.

By Rajat D

Oct 20, 2017

I really liked the case study based approach of this course. It makes you hit the ground running by applying the concepts learnt in a lesson in the case study immediately. I also like the light hearted tone of the teachers - Emily and Carlos, which helps in retaining interest through some of the more challenging concepts in the course.

By Sivashankar G

Jul 17, 2016

This course is the right choice for someone who wants to get a high-level overview of the various fundamental concepts in machine learning and provides the zeal to pursue further. Concepts have been explained by the lecturers really well and quizzes and assignments help us to validate our knowledge of the concepts in a seamless manner.

By Bharat R

Jul 30, 2017

This course is a great way to get adequately detailed knowledge of Machine Learning Algorithms. The approach to it (case study based) makes it so much more fun and enjoyable that you can really apply yourself to it. The professors have simplified the most complex topics and explained it amazingly well. Happy to have taken this course.

By Mesum R H

Oct 16, 2017

A very very awesome course with exceptional explanations for each machine learning paradigms and use cases. The best thing for the course was the case study approach. I am taking this approach to train my people as well but over all thank you Carlos and Lady.. for the effort. Really hands on python and machine learning experience (Y)