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學生對 华盛顿大学 提供的 Machine Learning: Classification 的評價和反饋

4.7
3,201 個評分
533 條評論

課程概述

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)....

熱門審閱

SM

Jun 15, 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 :)

SS

Oct 16, 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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426 - Machine Learning: Classification 的 450 個評論(共 502 個)

創建者 SAI V L

Jan 26, 2018

Some instructions in programming assignments are not clear.

創建者 charan S

Jul 30, 2017

Very nice course, detailed explanations and visualizations.

創建者 Sahil M

Jul 10, 2018

Was a good course with some in-depth topics covered!

創建者 Jiancheng

Mar 20, 2016

good course but too much easy, can be a good review.

創建者 Hanqiao L

Aug 09, 2016

Need more content for SVM and Random Forest

創建者 Alejandro T

Sep 09, 2017

It's a really good course, really liked it

創建者 Mohit G

Feb 02, 2019

Good, insightful but repetitive coding.

創建者 Sah-moo K

Apr 03, 2016

Decision trees and boosting were great.

創建者 Chitrank G

May 10, 2020

The course is excellent for beginners.

創建者 Gareth J

Aug 26, 2019

A good course to teach the key points.

創建者 Hexuan Z

Oct 06, 2016

could be more challengable homework!!

創建者 Vladislav V

May 13, 2016

It feels like it lacks certain depth.

創建者 Shashwat G

May 22, 2020

Course material can be much better

創建者 Farmer

Aug 12, 2018

Exercises are way too easy.

創建者 Aadesh N

Jun 14, 2016

Great course materials

創建者 Xiaojie Z

Jan 31, 2017

Can be more detailed.

創建者 Ragunandan R M

Sep 17, 2018

Good overall course.

創建者 Lim W A

Nov 21, 2016

Learnt new things.

創建者 Mehul P

Aug 17, 2017

Nice explanation.

創建者 gaozhipeng

Jul 01, 2016

good introduction

創建者 Alberto B

Mar 17, 2018

Very good course

創建者 Antonio P L

Apr 30, 2016

Fantastic Course

創建者 Anand B

Aug 07, 2017

Great course!

創建者 Ayswarya S

Feb 05, 2019

best course

創建者 Alberto J L R

Oct 12, 2017

Good Mooc