Chevron Left
Back to Machine Learning: Classification

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

4.7
stars
3,736 ratings

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

KL

Jun 23, 2017

Great course. I learned a lot about Classification theories as well as practical issues. The assignments are very informative providing complimentary understanding to the lectures.

IF

Jul 17, 2017

Good overview of classification. The python was easier in this section than previous sections (although maybe I'm just better at it by this point.) The topics were still as informative though!

Filter by:

301 - 325 of 589 Reviews for Machine Learning: Classification

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 12, 2016

So cool and much practical.

By Dr.M R

•

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

By MRS. G

•

May 9, 2020

GREAT LEARNING EXPERIENCE

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

By Brian N

•

May 20, 2018

Nice to learn this topic

By Mark h

•

Jul 26, 2017

Very Helpful Material!!!

By Shiva R

•

Apr 16, 2017

Exceptional and Intutive

By Shanchuan L

•

Dec 7, 2016

This is a perfect course

By Changik C

•

Oct 25, 2016

Learned a lot recommend!

By Alexander S

•

Aug 7, 2016

one of the best courses.

By Yacine M T

•

Jul 31, 2019

Very helpful. Thank you

By Fakhre A

•

Feb 17, 2017

Outstanding Course.....

By Weituo H

•

Mar 14, 2016

Useful and interesting~

By Gaurav K

•

Sep 19, 2020

Very good course to do

By GURUSUBRAMANI. S

•

May 24, 2020

Excellent Course.....

By Kevin Y

•

Jun 26, 2017

Very good instructors

By Sami A

•

May 20, 2016

The best in the field

By stephon_lu

•

Dec 23, 2017

very good! thank you