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

4.6
stars
13,380 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

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.

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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1051 - 1075 of 3,117 Reviews for Machine Learning Foundations: A Case Study Approach

By Ray

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Dec 19, 2016

This Course really helped me to understand the basic concepts in Machine Learning.

By Bill F

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Oct 1, 2016

Too much emphesis on graphlab. exercises should be prototyped and done in sklearn.

By Bakhtawar U R

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Apr 4, 2016

A Great course. Professors are enthusiastic and well acknowledged about the topic.

By 王先生

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Jan 9, 2016

This Course is really a great way to get knowledge of the simple machine learning.

By Alexander P

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Jul 21, 2021

Excelente que pasaran de Graphlab a Turicreate, dado que este ultimo es gratuito.

By Kishore K

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Jul 13, 2020

The course was really interesting and drills into the basics of machine learning.

By YASHKUMAR R T

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Mar 24, 2019

Best course to understand all the fundamentals of machine learning for beginners.

By Arul T

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Sep 6, 2017

Excellent lessions to start with..Gifted to be part of these sessions.Very nice..

By Andrey U

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Mar 10, 2016

Really great approach with a lot of useful and easy to get info. Really loved it!

By Nickil M

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Nov 6, 2015

Enjoyed thoroughly.Nice way of implementing various tasks using ipython notebook.

By Caleb B

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Dec 15, 2020

Great material and instruction. Very practical application as well. Well done!

By Adel M

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Aug 29, 2020

this course is great for an introduction to ML, and the approach used is amazing

By Jeevanantham C

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Jun 14, 2020

Good learned basic case study approach of various sectors using machine learning

By Kuan-Wen C

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Jul 21, 2019

high level overview of ML. Good for people who want to know about ML intuitively

By Ashish S

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Apr 23, 2017

A very good and user friendly course . The practical examples are of great help.

By Sameer M

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Feb 8, 2017

Excellent Course! Must do for everyone who wants to start with machine learning.

By Ecaterina M

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Oct 28, 2016

Incredibly helpful for somebody with no previous experience in machine learning.

By igamenovoer

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Apr 29, 2016

excellent material for getting a feel of different machine learning applications

By Daniel M

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Dec 23, 2015

I love this course. I found it informative and the materials easy to understand.

By Faith S C

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Sep 20, 2021

I love the manner in which the concepts were explained. Beautiful slides too!!

By Masrur A P

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Jul 23, 2021

Such a really nice course to learn. From here I learned many important things.

By Pablo V

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Nov 23, 2020

It was beyond my expectations. I'm already looking forward to the next courses.

By Hadeer T

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Aug 1, 2020

it was very useful to me to join this course really thank you for your efforts.

By Kishore S

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Dec 22, 2019

Lecturer explained the course very clearly and course designed really excellent

By George

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Dec 12, 2019

the course has been very helpful in my development in the field of data science