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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
3,117 個評分
519 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

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!

CJ

Jan 25, 2017

Very impressive course, I would recommend taking course 1 and 2 in this specialization first since they skip over some things in this course that they have explained thoroughly in those courses

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151 - Machine Learning: Classification 的 175 個評論(共 487 個)

創建者 Jifu Z

Jul 23, 2016

Good class, But it would be much better if the quiz is open to those who doesn't pay.

創建者 Sanjay M

Jun 30, 2017

Very nice course with good mix of machine learning concepts with maths, programming.

創建者 Saheed S

Jul 18, 2017

It was a great course, I will start working on a new classification project. Thanks

創建者 Darryl L

Oct 27, 2016

they do a good job explaining concepts in great detail so everyone can learn it.

創建者 Ning Z

Mar 20, 2016

Great way of teaching, technical details well demystified. Thank you very much!

創建者 Michael O T

Nov 30, 2019

A great professor and a lot of knowledge about machine learning classification

創建者 Suresh K P

Dec 19, 2017

This course much helpful and understandable easily compared previous sessions.

創建者 Daopeng S

Apr 12, 2016

A very good introduce machine learning course, it's clear and easy to follow.

創建者 Daniel Z

Mar 08, 2016

This is a hand-on very exciting course, strongly recommended for all audience

創建者 Vladimir V

Jun 14, 2017

Awesome course! Highly recommend for anyone interested in machine learning.

創建者 James M

Jul 20, 2016

Top notch. Great course design. Best value for money in Machine Learning!

創建者 Javier A

Nov 25, 2018

Quite Interesting. Entertaining and the lectures are quite easy to follow.

創建者 kazi n h

Jun 23, 2016

One of the awesome course on classification. Just so perfect for learning.

創建者 Chandan D

Aug 25, 2018

I really enjoyed learning this course on Machine Learning Classification!

創建者 Zuozhi W

Feb 09, 2017

Very informative class! The lectures are slow, clear, and easy to follow.

創建者 Pankaj K

Sep 25, 2017

Great challenging and deep assignments! Big Thanks to both professors!!

創建者 Zhongkai M

Feb 12, 2019

Great course, provided details that not show in others' and textbooks.

創建者 Courage S

Oct 22, 2018

Excellent Teaching with meticulous details and great humor. BIG Plus.

創建者 Tewende J E K

Jul 24, 2016

intuitive, clear and practical. The best explanation I found so far !

創建者 akashkr1498

May 19, 2019

good course but make quize and assignment quize more understandable

創建者 Alexandre N

Dec 20, 2016

Excellent course with plenty of intuition and practical experiments.

創建者 eric g

Mar 21, 2016

The best part for me in this specialization, Classification is great

創建者 Karthik M

Jun 01, 2019

Excellent course and the instructors cover all the important topics

創建者 Srinivas J

Nov 12, 2016

truly enjoyed this course and recommended to my colleagues as well.

創建者 Thierry Y

Nov 12, 2017

Great material, easy to follow, and nice examples around sushis :)