Chevron Left
Voltar para Machine Learning: Classification

Comentários e feedback de alunos de Machine Learning: Classification da instituição Universidade de Washington

3,118 classificações
519 avaliações

Sobre o curso

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)....

Melhores avaliações


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!


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

Filtrar por:

251 — 275 de {totalReviews} Avaliações para o Machine Learning: Classification


Jun 14, 2017

Best ML course I've ever taken!

por Sandeep K S

May 07, 2016

awesome course awesome teachers

por Vijai K S

Mar 05, 2016

Heck yeah!! its finally here :D

por Jinho L

Jul 20, 2016

Very pragmatic and interesting

por Snehotosh K B

Mar 20, 2016

Excellent and very intuitive.

por Neemesh J

Oct 28, 2019

Awesome learning experience.

por Fan J

Aug 04, 2019

good content, help me a lot!

por Mike M

Jul 16, 2016

Learned a lot, great course!

por Dwayne E

Dec 21, 2016

Awesome course learned alot

por Rui W

Sep 13, 2016

So cool and much practical.

por kumar A

Jun 05, 2018

great course for beginners

por Lixin L

May 07, 2017

really good course. thanks

por MRS. G

May 09, 2020


por Satish K D

Feb 03, 2019

it was easy to understand

por FanPingjie

Dec 09, 2018

useful and helpful course

por Lars N

Oct 04, 2016

Best course taken so far!

por Venkata D

Apr 14, 2016

Great course and learning

por Brian N

May 20, 2018

Nice to learn this topic

por Mark h

Jul 27, 2017

Very Helpful Material!!!

por Shiva R

Apr 16, 2017

Exceptional and Intutive

por Shanchuan L

Dec 07, 2016

This is a perfect course

por ChangIk C

Oct 25, 2016

Learned a lot recommend!

por Alexander S

Aug 07, 2016

one of the best courses.

por Yacine M T

Jul 31, 2019

Very helpful. Thank you

por Fakhre A

Feb 17, 2017

Outstanding Course.....