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

4.6
stars
13,231 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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376 - 400 of 3,071 Reviews for Machine Learning Foundations: A Case Study Approach

By Kishlay K

Mar 2, 2021

I learned a lot of new things here, this was my first course on ML.

A lots of new ideas and their implementations, I learned which not

only enhanced my knowledge but also helped me in preparation for

becoming useful and worthwhile.

THANKYOU!!

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 Deepali S

Jul 13, 2020

the professors are very interactive and keep the lectures fun. all the programming assignments really helps in understanding the concepts. totally recommended for anyone who is new to machine learning and wants to explore all its aspects.

By CARLOS O T G

Apr 7, 2021

It's an excelent basic course about Machine Learning, however, I think that I need to learn more advanced features, like controlling the number fo nodes and layers of the neural networks, but I think that would be in an advanced course.

By Taylor N

Dec 20, 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 Leor A R

Feb 13, 2021

Great course, Emily and Carlos teach this class in a very interest way. They try to let student understand

machine learning by some case study. That worked well for me. For me the GraphLab wasn't that

good but you can use other packages.

By Sumedh S M

May 7, 2020

It's a go-to course for all the learners who want to get an idea of what the emerging field of Machine Learning is about. Well structured and well delivered. Everything from the lectures to assignments helped me grasp all the concepts.

By Abhinav U

Nov 1, 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 G

Jul 6, 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 1, 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 Leonardo L

Aug 1, 2020

The course has an excellent approach to ML theory and practice. The TuriCreate Framework helps to increase the learning speed and depth of the classes. Congratulations to the Professors and I'm excited to continue the specialization.

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 Bernd D

Mar 18, 2022

As a primer on ML, to get an overview over the key concepts and plenty of hands on experience, I absolutely enjoyed the course and can highly recommend it. Looking forward to continue with the next course in this specialisation.

By Anshumaan S

Feb 1, 2022

I am not exaggerating when I say this has been a course I thoroughly enjoyed compared to some other courses I have done, with get content and instructors. Looking forward to starting the other courses in this specialization ASAP!

By Miguel R

Jun 4, 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 R

Apr 1, 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 5, 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 14, 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.