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
13,527 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

SZ

Dec 19, 2016

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 on me. I like this course very much.

Filter by:

776 - 800 of 3,156 Reviews for Machine Learning Foundations: A Case Study Approach

By andreas c c

Mar 15, 2017

I really enjoyed the course! IVery practical and straightforward,we dive to Ml right away.

Amazing instractors and very funny.

By Johannes C

Oct 1, 2016

The hands-on exercises were really fun and brought a lot of insight. The material was presented in a very understandable way.

By Adriana M R C

May 9, 2016

I truly enjoyed this course, its "case study" approach and its "hands on" learning activities. I expect to continue this spec

By Mark T

Dec 31, 2015

Awesome material and organization. Also, real fun chemistry between the two instructors (they MUST be married or something!)

By Vikash C S

Nov 15, 2015

I am currently taking this course and I find this approach (case study approach) very effective in learning on MOOC platform.

By Shyam S K (

Sep 29, 2015

The Best Thing About Case Based Study is That You See The Things Actually Happening And Nothing Feels More Good Than That :))

By Alejandro A J

May 25, 2021

Great course, it shows the basics of machine learning with several assingments that are enough to prove what you have learn.

By Praveen B

Nov 27, 2018

The professors have taken it in a fun filled way. The material is also very interesting. This is an experience worth having.

By Kurt K

Dec 24, 2015

Good introduction course providing nice overview of topics to be seen more in detail in the remaining of the specialization.

By Rowen

Oct 28, 2015

Teachers are really nice. Materials and the teaching are fantastic, I really learned a lot from this course. Thanks so much.

By Rubén A S M

Oct 8, 2015

Amazing and very entertaining introduction to Machine Learning. It has interesting labs and the theory is explained clearly.

By DANIEL R

Jul 13, 2020

it was a really good course with practical examples. I Recommend to all those who wants to get into machine learning world!

By Narayana S A

May 31, 2020

Incredible course, super cool instructors, worth taking every bit. Thanks to both the instructors. Turicreate used is good.

By biqing w

May 7, 2020

give a clear big picture of different models in machine learning on a vivid way by solving practical problem in daily work.

By Siyue

Sep 28, 2017

Great lecture and clear demonstration in both theoretical and practical manner! I will recommend this course to my friends!

By Nikhil J

Feb 24, 2016

The Case study approach helped me quickly get an overview of the usage of Machine Learning techniques in a very short time!

By 何振炜

Feb 22, 2016

It's pretty good class that give a quick understanding of what Machine Learning is. It simple but not easy. Really amazing!

By Chaitanya B

Nov 21, 2015

A good overview of all different classes of algorithms. More engineering oriented than math / statistics behind the scenes.

By Ziliang W

Oct 16, 2015

Fantastic course, the professors are awesome, the assignments are great, cannot wait to see the upcoming following courses.

By Saurabh A

Jul 9, 2020

good, but it was very difficult to install turicreate and other required tools. please provide a dedicated video for that.

By Chao T

Jan 7, 2020

This course is great. I have a good understanding of Machine Learning concepts and algorithms during this studying period.

By xncoursera

Aug 21, 2019

This course is my first course in the direction of machine learning, it has a great impact on me, I learned a lot from it.

By 刘扬

Aug 8, 2017

直接上案例,通过案例与常用算法进行结合,使得我们理解算法更加直观有效,后续课程应该是要对本课中提到的算法进行详解,通过这种方式,能够首先打下直观理解的基础,再通过细致研究,这种自上而下的方式使得我们对机器学习的整个框架达到一个更高的level。

By Juliane H

Jul 26, 2017

Really enjoyed the course, might be low demanding if you habe prior python/statistic knowledge, but still great for noobs!

By Dharmesh P

Oct 17, 2016

This was a very well put together course. I like how they walk you through each of the exercises if you need help. Thanks.