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Voltar para Machine Learning: Regression

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

4.8
estrelas
5,314 classificações
992 avaliações

Sobre o curso

Case Study - Predicting Housing Prices In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression. In this course, you will explore regularized linear regression models for the task of prediction and feature selection. You will be able to handle very large sets of features and select between models of various complexity. You will also analyze the impact of aspects of your data -- such as outliers -- on your selected models and predictions. To fit these models, you will implement optimization algorithms that scale to large datasets. Learning Outcomes: By the end of this course, you will be able to: -Describe the input and output of a regression model. -Compare and contrast bias and variance when modeling data. -Estimate model parameters using optimization algorithms. -Tune parameters with cross validation. -Analyze the performance of the model. -Describe the notion of sparsity and how LASSO leads to sparse solutions. -Deploy methods to select between models. -Exploit the model to form predictions. -Build a regression model to predict prices using a housing dataset. -Implement these techniques in Python....

Melhores avaliações

PD
16 de Mar de 2016

I really enjoyed all the concepts and implementations I did along this course....except during the Lasso module. I found this module harder than the others but very interesting as well. Great course!

KM
4 de Mai de 2020

Excellent professor. Fundamentals and math are provided as well. Very good notebooks for the assignments...it’s just that turicreate library that caused some issues, however the course deserves a 5/5

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951 — 959 de 959 Avaliações para o Machine Learning: Regression

por Eugene K

10 de Fev de 2017

If you are considering this specialization I would recommend the Andrew Ng course instead and the main reason is that it isn't depend on proprietary ML framework. Despite the good lectures, the assignments don't help you develop the knowledge required for ML developer role.

Taking in consideration the permanent postponing the courses delivery, from summer 2016 to summer 2017, finally the most interesting part of the specialization was cancelled. I'm completely disappointed with the specialization learning expirience.

por William S

3 de Mai de 2016

This course is structured around a specific and costly Python library called Dato. It is possible to do the homework without it, but it is EXTREMELY difficult to do so. If the course wasn't structured around using Dato, it would be a lot simpler and a easier to complete the assignments. Also, a lot of the mathematical notation was written in a kind of psuedo Python code that made things confusing sometimes.

por Mats W

17 de Dez de 2016

The lecturers try to keep the instructions basic and pedagogical. Pretty good. Everything in this revolves around a tool graphlab create. Not so great, I think. It is not free (you get a one year licence) and hides all the action from the user. I don't like that the course then makes me feel that I must rely on a specific product to solve problems.

por Konstantin K

19 de Jun de 2016

I was not aible to complete this course for free. That was very disappointing! Universities like Stanford and John Hopkins find the opportunity to offer similar courses free of charge to peoople who want to learn. From University of Washington I have expected the same. Your bad!

Best regards

Konstantin

por Ehsan M

10 de Mar de 2018

The teachers have a great success in developing Tori, but, the teaching is not good. The way machine learning is presented is mixed, and all over the place.

Not worth to put time on

por Om G

14 de Ago de 2020

I saw the whole course.

I didn't get anything.

Maybe you can just increase some videos and explain neatly.

por Andreas

4 de Jan de 2017

This specialization is delayed for months now - very annoying! Don't give them money!

por Adrien L

2 de Fev de 2017

No good without the missing course and capstone projects

por Ken C

4 de Fev de 2017

Not happy about course 5 & 6 got cancelled.