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Learner Reviews & Feedback for Machine Learning: Classification by University of Washington

3,611 ratings
597 reviews

About the Course

Case Studies: Analyzing Sentiment & Loan Default Prediction In our case study on analyzing sentiment, you will create models that predict a class (positive/negative sentiment) from input features (text of the reviews, user profile information,...). In our second case study for this course, loan default prediction, you will tackle financial data, and predict when a loan is likely to be risky or safe for the bank. These tasks are an examples of classification, one of the most widely used areas of machine learning, with a broad array of applications, including ad targeting, spam detection, medical diagnosis and image classification. In this course, you will create classifiers that provide state-of-the-art performance on a variety of tasks. You will become familiar with the most successful techniques, which are most widely used in practice, including logistic regression, decision trees and boosting. In addition, you will be able to design and implement the underlying algorithms that can learn these models at scale, using stochastic gradient ascent. You will implement these technique on real-world, large-scale machine learning tasks. You will also address significant tasks you will face in real-world applications of ML, including handling missing data and measuring precision and recall to evaluate a classifier. This course is hands-on, action-packed, and full of visualizations and illustrations of how these techniques will behave on real data. We've also included optional content in every module, covering advanced topics for those who want to go even deeper! Learning Objectives: By the end of this course, you will be able to: -Describe the input and output of a classification model. -Tackle both binary and multiclass classification problems. -Implement a logistic regression model for large-scale classification. -Create a non-linear model using decision trees. -Improve the performance of any model using boosting. -Scale your methods with stochastic gradient ascent. -Describe the underlying decision boundaries. -Build a classification model to predict sentiment in a product review dataset. -Analyze financial data to predict loan defaults. -Use techniques for handling missing data. -Evaluate your models using precision-recall metrics. -Implement these techniques in Python (or in the language of your choice, though Python is highly recommended)....

Top reviews

Jun 14, 2020

A very deep and comprehensive course for learning some of the core fundamentals of Machine Learning. Can get a bit frustrating at times because of numerous assignments :P but a fun thing overall :)

Oct 15, 2016

Hats off to the team who put the course together! Prof Guestrin is a great teacher. The course gave me in-depth knowledge regarding classification and the math and intuition behind it. It was fun!

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276 - 300 of 566 Reviews for Machine Learning: Classification

By Fernando B

Feb 21, 2017

Best Course on ML yet on the Web

By Pranas B

Jul 1, 2016

Good practice and bit of theory.

By Andrew M

Jun 15, 2016

I came here to learn. I learned.

By zhenyue z

Jun 3, 2016

good lecture, good for everyone.

By Pakomius Y N

Sep 28, 2020

Sangat Bermanfaat,Terima Kasih.

By Manuel T F

Jul 21, 2017

Really great course. Well done!

By tonghong c

Jun 14, 2017

Best ML course I've ever taken!

By Sandeep K S

May 7, 2016

awesome course awesome teachers

By Vijai K S

Mar 5, 2016

Heck yeah!! its finally here :D

By Vinothkumar G

Jul 11, 2020

Very useful learning platform.

By Jinho L

Jul 20, 2016

Very pragmatic and interesting

By Snehotosh B

Mar 20, 2016

Excellent and very intuitive.

By Neemesh J

Oct 28, 2019

Awesome learning experience.

By Fan J

Aug 3, 2019

good content, help me a lot!

By Mike M

Jul 16, 2016

Learned a lot, great course!

By Dwayne E

Dec 20, 2016

Awesome course learned alot

By Rui W

Sep 13, 2016

So cool and much practical.

By Ramkumar M

Jun 26, 2021

Very Useful for my carrier

By kumar a

Jun 5, 2018

great course for beginners

By Lixin L

May 7, 2017

really good course. thanks


May 9, 2020


By Satish K D

Feb 3, 2019

it was easy to understand

By FanPingjie

Dec 9, 2018

useful and helpful course

By Lars N

Oct 4, 2016

Best course taken so far!

By Venkata D

Apr 14, 2016

Great course and learning