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

3,670 個評分


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)....




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 :)



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!


176 - Machine Learning: Classification 的 200 個評論(共 575 個)

創建者 Darryl L


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

創建者 Ning Z


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



Its a very usefull course to understand the machine learning in a easiest way.

創建者 Shawon P


A must take course for every individual trying to understand Machine Learning.

創建者 Michael O T


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

創建者 Suresh K P


This course much helpful and understandable easily compared previous sessions.

創建者 Daopeng S


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

創建者 Daniel Z


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

創建者 Xavi R


This is a great course! The professors are great and the material is clear!

創建者 Vladimir V


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

創建者 James M


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

創建者 Javier A


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

創建者 Kazi N H


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

創建者 Chandan D


I really enjoyed learning this course on Machine Learning Classification!

創建者 Zuozhi W


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

創建者 Pankaj K


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

創建者 Zhongkai M


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

創建者 courage s


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

創建者 Jean-Etienne K


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

創建者 akashkr1498


good course but make quize and assignment quize more understandable

創建者 Alexandre N


Excellent course with plenty of intuition and practical experiments.

創建者 eric g


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

創建者 Swapnil A


Really awesome course. Dr. Carlos explains everything from scratch.

創建者 Karthik M


Excellent course and the instructors cover all the important topics

創建者 Srinivas J


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