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Machine Learning: Classification に戻る

ワシントン大学（University of Washington） による Machine Learning: Classification の受講者のレビューおよびフィードバック

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3,542件の評価
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588件のレビュー

コースについて

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)....

人気のレビュー

SM
2020年6月14日

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
2016年10月15日

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!

フィルター：

Machine Learning: Classification： 301 - 325 / 556 レビュー

by Fakhre A

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2017年2月17日

Outstanding Course.....

by Weituo H

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2016年3月14日

Useful and interesting~

by Gaurav K

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2020年9月19日

Very good course to do

by GURUSUBRAMANI. S

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2020年5月24日

Excellent Course.....

by Kevin Y

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2017年6月26日

Very good instructors

by Sami A

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2016年5月20日

The best in the field

by stephon_lu

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2017年12月23日

very good! thank you

by Michael P

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2016年12月6日

Awesome, not awful;)

by 쥬

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2016年6月30日

It's very practical.

by AJAY K

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2019年10月13日

Excellent tutorials

by Muhammad Z H

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2019年8月30日

I have learned alot

by Luis E T N

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2017年7月4日

Excelent! Congrats!

by Itrat R

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2017年1月22日

Excellent Course!!!

by Roger S

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2016年9月4日

This course is COOL

by Ankit S

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2016年6月8日

Really nice course!

by N P

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2020年7月20日

wonderful lectures

by Mrs. G A D

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2020年5月13日

Wonderful learning

by Sandeep J

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2016年9月4日

Its s great course

by Kurt K

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2016年4月16日

Excellent course !

by DEEPAK P

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2020年6月6日

ULTIMATE TEACHING

by Aparna g

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2020年1月30日

very Good Concept

by Germanno T

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2019年12月4日

Excellent Course!

by Miguel Á B P

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2019年5月21日

Excellent course!

by parv j

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2019年3月3日

Brilliant course!

by Mayank C

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2018年4月12日

Loved this course

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