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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

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!

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.

筛选依据：

276 - Machine Learning: Classification 的 300 个评论（共 589 个）

创建者 Komal Y

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Nov 12, 2024

good for knowledge, i learned alot

创建者 Cosmos D I

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Mar 29, 2020

This course is very informational!

创建者 Alessandro B

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Oct 31, 2017

nice, clear engaging ...and useful

创建者 易灿

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Nov 27, 2016

课程很生动，讲的很详细，真心谢谢导师！希望能在算法后面多提供点资料！

创建者 Henry H

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Nov 17, 2016

Very clear and easy to understand.

创建者 Angel S

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Mar 8, 2016

Awesome. Waiting for the next one.

创建者 Jing

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Aug 14, 2017

Better than the regression course

创建者 Rishabh J

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Dec 19, 2016

Amazing course, Amazing teaching.

创建者 CHERUKURI S V N K

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May 29, 2020

IT WAS EXCELLENT AND ENJOYED IT.

创建者 Fernando B

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Feb 21, 2017

Best Course on ML yet on the Web

创建者 Pranas B

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Jul 1, 2016

Good practice and bit of theory.

创建者 Andrew M

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Jun 15, 2016

I came here to learn. I learned.

创建者 zhenyue z

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Jun 3, 2016

good lecture, good for everyone.

创建者 Pakomius Y N

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Sep 28, 2020

Sangat Bermanfaat,Terima Kasih.

创建者 Manuel T F

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Jul 21, 2017

Really great course. Well done!

创建者 tonghong c

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Jun 14, 2017

Best ML course I've ever taken!

创建者 Sandeep K S

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May 7, 2016

awesome course awesome teachers

创建者 Vijai K S

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Mar 4, 2016

Heck yeah!! its finally here :D

创建者 Định H

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Apr 23, 2024

Number of assignment is huge !

创建者 Vinothkumar G

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Jul 11, 2020

Very useful learning platform.

创建者 Jinho L

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Jul 19, 2016

Very pragmatic and interesting

创建者 Snehotosh B

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Mar 20, 2016

Excellent and very intuitive.

创建者 Neemesh J

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Oct 27, 2019

Awesome learning experience.

创建者 Fan J

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Aug 3, 2019

good content, help me a lot!