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

4.6
stars
13,374 ratings

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 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

PM

Aug 18, 2019

The course was well designed and delivered by all the trainers with the help of case study and great examples.

The forums and discussions were really useful and helpful while doing the assignments.

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351 - 375 of 3,115 Reviews for Machine Learning Foundations: A Case Study Approach

By Raphael K

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Feb 29, 2016

Nice class, give a brief introduction to all the methods use in ML without going deep. If you just want to get an idea of what ML Technics are and how to implement them this course is for you. If you are want more technical details about ML this class is not for you.

By Yaobang C

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Aug 29, 2018

I am very grateful to the coursera platform for giving me the opportunity to learn, and I would also like to thank the two professors for their careful preparation of the wonderful lectures. I learned about machine learning and fell in love with ipynb, thanks again!

By Jose N N P

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Mar 30, 2018

Excellent course and very challenging, most importantly, I have learned a lot and I have a great understanding of what machine learning is. Dr. Carlos and Emily are great instructors, and indeed engaging as well as passionate. Looking forward to taking the next one.

By Easton L

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Feb 25, 2017

Emily and Carlos are really exciting teachers. This course covers fundamental concepts of Machine Learning and comes with very practical assignments. I've learned a lot from the this course and I believe it will make me ready for more challenging work in the future.

By Alan B

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May 14, 2020

Material was presented in a practical way, making it useful to relate the theoretical concepts to real life applications.

One suggestion might be to speed up the video while typing comments and mistakes while typing, etc. just to make the experience more enjoyable.

By Martin K

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Mar 26, 2016

First of all I want to thank you for conducting this course. I have learned a lot from the course. This course gave me basics understanding of machine learning. You did a good job presenting complex machine learning algorithms in a way that everyone can understand.

By don-E M

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Dec 13, 2015

I have loved this course. The approach to learning is most fruitful as I have learned a great deal and had a lot of fun along the way. I am on the last exercise to finish the class after about 4 days. I am going to savor this last one because this was too much fun.

By Anatoly M

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Apr 16, 2017

Great introduction to machine learning, not too much math but gives a good idea of what ML is + gives practice in Python (which was my initial goal).

The tests contained a few inaccuracies (they didn't completely match on my machine/setup), but otherwise was fine.

By Ravindra P

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May 26, 2020

Great Course to start with machine learning. When I started this course I heard bad words about turicreate. But I think it is very easy to work with this compare to pandas. And it will even save your time that you can invest in learning more theoretical aspects.

By Vinay S

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Jun 1, 2016

Very interesting and fun course for really complicated topic. The best part of the course is the recommended software tools they are brilliant designed especially graphlab.create. Both the instructors are really engaging and teach complicated topics really well.

By Ravindra M

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Dec 8, 2015

Case study approach works !

I completed this course and found course materials present intuitive. Following courses go deep in each method.

Thank you Emily and Carlos :-)

A small request to Coursera to provide course completion certificate to free account like Edx.

By Varun M

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Mar 12, 2018

The course starts from very basic level and allows to apply the knowledge practically right from the start so the learner can start to see the results right away which makes it interesting and addictive to jump to next session or video to gain more knowledge.

By Rick P

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Aug 13, 2016

Emily and Carlos provide a very fun and informative introduction to ML! I really appreciated getting a "blackbox" overview of the various ML methods before doing a deep dive into the algorithms. GraphLab and the interactive iPython sessions are great!

By mohammed e e

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Feb 8, 2016

it's the best course of machine learning i'have token in my life,the method of teaching is great, the content is really fantastic, the instructors teaching skill is excellent and it cover lots of real world artificial applications so it's very amazing

By Vikram V

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Sep 28, 2016

Excellent course and excellent way to learn machine learning. The professors are great and the exercises are challenging. I love the way the professors teach the course using case study approach, that makes it all the more interesting and fun to learn

By Caio L F

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May 24, 2018

Excellent course for those who wants to start to understand what really machine learning is. It goes beyond the theorical part, with pretty cool exercises. The case studies help us to visualize how the many applications we see at the real world work.

By Marcio R

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Feb 23, 2016

Excellent introduction and refresher in ML, this course talks in a broad range about the ML applications, and the areas surrounding it. Even if you dont plan to follow the entire Especialization, this is still a very good introduction to the subject.

By Hamed A

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Jul 17, 2022

I like the fact that the instructors kept giving intuitions and theories behind with a strong focus on real-world applications. Definitely enjoyed the general intro to ML, and am curious to see how the next courses in this specialization look like.

By Deleted A

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Oct 9, 2018

Thank you for the amazing course. To be honest this is the first course that I complete on course era. The professors are amazing and the pace of learning is suitable for all levels. I look forward to complete the whole specialization. Keep going :)

By Tim C

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Dec 21, 2015

Very enthusiastic lecturers and good resources to learn from. The only thing to consider before taking the course is to learn a little bit of python, as well as having the GraphLab guide to look up for functions.

Best course I've studied in Coursera.

By Farooq M K

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Oct 1, 2016

Very thoughtfully and beautifully created course. Both the teachers are really wonderful and know how to explain something so difficult in a very easy to understand language.

Thankyou for making it so easy and at the same time very very interesting.

By Tianqi Z

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Aug 9, 2016

Very good for practicing! It seems to be very easy when you just watch the lectures but after you do the homework you will soon change your mind because the homework is of high quality and can help grasp the working skills for machine learning job.

By Salman M

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Jul 15, 2016

It's a basic machine learning course for new learners who want to explore what Machine Learning is. This course is a setup for the rest of the specialization and requires various guided programming exercises covering the most popular ML algorithms.

By Deleted A

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Feb 27, 2016

Excellent course for anybody from a college student to a senior Executive who not only wants to understand what Machine Learning is but also how it works and can help! Looking forward to rest of the courses in the Machine Learning Specialization...

By TAMERA Y

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May 16, 2017

Really enjoyed the course. This was a great course for someone who has never taken Machine Learning Or Python. I found the Graphlab Note book very helpful. Plus I loved having the opportunity to write the code / algorithms with Carlos. Great Co