Chevron Left
Back to Machine Learning Foundations: A Case Study Approach

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

4.6
stars
9,241 ratings
2,203 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

Filter by:

251 - 275 of 2,121 Reviews for Machine Learning Foundations: A Case Study Approach

By Abhishek M

Aug 10, 2016

The course covers wide range of topics along with the real world examples in simple language , The assignments are superb, they help you to grasp the concepts in much detail and sets a strong foundation . Would definitely recommend this course.

By Stefano T

Nov 30, 2015

The course is very intuitive and easy to follow; nevertheless it never falls in banality. It really gives you the wish to dive deeper in the machine learning world.

A big thanks to both teachers; their love for this science is very contagious!!!

By Samuel d Z

Jun 17, 2017

Great Course, so much valuable information and in combination with Python/Graphlab, I think it is perfect when starting out on ML. Looking forward to the other 3 courses in this series. Lectures are both perfect and tempo is exactly as needed.

By Ghiath Z

Dec 12, 2015

I really like this course, it helps me to ramp up with machine learning topic. moreover, it keens me to continue the specialization and dive with the notions mentioned on the lecture, and i won't forget to thank the lecturers Emily and Carlos.

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

By Shouvik R

Nov 27, 2016

This was a great introduction to the field of machine learning. Full with practical examples and hands on homework the course really catered to my learning style. Although the initial weeks were easy, the last week gets pretty challenging.

By Taylor N

Dec 21, 2015

Great opener, and I learned some good algorithms that I can already apply. Really liked how they walked you through every problem for the quizzes too--the later course was not like that, a bit more difficult with the quizzes, for sure.

By Abhinav U

Nov 01, 2015

Liked the interactive exercises and coding assignments, you can actually play with your own datasets using the ideas shown in the course and learn to apply the concepts. The course is really very basic but can be a good starting point.

By Jafed E

Jul 06, 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

By Wilmer S C

Jul 10, 2017

I think it is a very useful starter course to dive into Machine Learning concepts and a little bit of practice. I am looking forward to the next course to begin implementing and of course, understanding more thoroughly these concepts.

By piyush s

Nov 01, 2015

Excellent course. I would have preferred sample code with Skitlearn and other Python packages as well because I believe still 95 % of the people use those. I liked the Sframe but I don't see right now many people using it in industry.

By Michael H

Jul 21, 2016

Really great introduction to machine learning and the various methods used. I really liked the length/structure of the lectures and found the assignments to be fun. I also really liked the dynamic the presenters have with each other.

By Daniel V

Mar 27, 2016

An easy, not simple, but humorous approach to a broad topic with practical samples that you can build on for further studies. Good for newbies as well as a fresh up for advanced applicants. Looking forward to the follow up courses.

By Andrew R

Jan 19, 2016

Great overview of different machine learning techniques. You don't learn much about implementing the individual techniques in this class, but you get a broad overview of many different techniques, which is the point of this class.

By Miguel R

Jun 04, 2019

Muy útil para empezar a conocer los conceptos básicos de machine learning, con casos comprensibles y útiles a través de python.

Los vídeos son muy explicativos y la corta duración de cada uno permite adaptarlo a cualquier horario.

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 Thomas K

Apr 01, 2018

very nice, no bull-shit introduction into main concepts from a practical perspective. It showed both easily exploitable possibilities in the field of ML as well as the outline of a huge horizon which might reach far beyond this.

By jose l v

Dec 05, 2015

This is a very practical an easy way to understand what is behind the ML world. Also, there are a set of tools in this course that would let you implement basic smart applications. I am ver pleased for being part of this course.

By Deleted A

Sep 16, 2016

I really enjoyed this course. The case study approach and the IPython hands-on gave a good understanding of the concepts discussed in the lecture videos. I'm looking forward to complete the specialization. Highly Recommended!!

By Patrick N

Feb 18, 2018

I enjoyed this course as a high-level overview of the basics of machine learning. While I liked the use of Jupyter and Python in general, I would have preferred that the course use scikit-learn. Overall, solid and fun course!

By Adil A

Dec 15, 2017

People who likes top-down learning approach should start ML from this course.

Instructors explain basic overview then follow with interesting practical tasks that makes you understand the topic much better.

Highly recommended.

By Gustavo S

Oct 30, 2016

Very cool course. I can say is the best course for intro to a big science called machine learning, have a lot of good real life examples, with gread mathematical understaing of how things works, i thinks is really cool course

By Varun S

Feb 08, 2016

It was indeed a very well designed course that not only gave a great overview of various machine learning techniques, but also gave hands-on experience in implementing those techniques. Loved Dato. GraphLab Create is awesome.

By Sergey T

Jan 03, 2016

It was instructive, easy to follow and fun to learn! Great thanks to Carlos Guestrin and Emily Fox for creating this excellent course! And thanks Coursera for making the high quality educational content available to everyone.

By 陆恩哲

Oct 15, 2017

A very great course !!!!! Two teachers are doing a good job. They use a kind of practical way, case-study, to teach me lots of practical machine learning knowledge. I will learn the next three courses in this specialization.