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学生对 University of Washington 提供的 Machine Learning: Classification 的评价和反馈

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3,737 个评分

课程概述

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)....

热门审阅

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.

DF

Aug 6, 2016

Not as good as the previous courses in this specialization - I agree with those who have noted that this one seemed a little rushed. However, these are still the best courses I've found on Coursera.

筛选依据：

301 - Machine Learning: Classification 的 325 个评论（共 589 个）

创建者 Mike M

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Jul 16, 2016

Learned a lot, great course!

创建者 Dwayne E

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Dec 20, 2016

Awesome course learned alot

创建者 Rui W

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Sep 12, 2016

So cool and much practical.

创建者 Dr.M R

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Jun 26, 2021

Very Useful for my carrier

创建者 kumar a

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Jun 4, 2018

great course for beginners

创建者 Lixin L

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May 7, 2017

really good course. thanks

创建者 MRS. G

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May 9, 2020

GREAT LEARNING EXPERIENCE

创建者 Satish K D

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Feb 2, 2019

it was easy to understand

创建者 FanPingjie

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Dec 9, 2018

useful and helpful course

创建者 Lars N

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Oct 4, 2016

Best course taken so far!

创建者 Venkata D

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Apr 14, 2016

Great course and learning

创建者 Brian N

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May 19, 2018

Nice to learn this topic

创建者 Mark h

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Jul 26, 2017

Very Helpful Material!!!

创建者 Shiva R

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Apr 16, 2017

Exceptional and Intutive

创建者 Shanchuan L

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Dec 7, 2016

This is a perfect course

创建者 Changik C

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Oct 25, 2016

Learned a lot recommend!

创建者 Alexander S

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Aug 7, 2016

one of the best courses.

创建者 Yacine M T

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Jul 31, 2019

Very helpful. Thank you

创建者 Fakhre A

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Feb 17, 2017

Outstanding Course.....

创建者 Weituo H

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Mar 13, 2016

Useful and interesting~

创建者 Gaurav K

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Sep 19, 2020

Very good course to do

创建者 GURUSUBRAMANI. S

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May 23, 2020

Excellent Course.....

创建者 Kevin Y

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Jun 26, 2017

Very good instructors

创建者 Sami A

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May 19, 2016

The best in the field

创建者 stephon_lu

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Dec 23, 2017

very good! thank you