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Opiniones y comentarios de aprendices correspondientes a Machine Learning: Regression por parte de Universidad de Washington

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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....

Principales reseñas

KM

4 de may. 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

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!

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301 - 325 de 984 revisiones para Machine Learning: Regression

por Deepak K S

18 de nov. de 2016

Great Course! Complex things explained in simple ways. Challenging Assignments helped in reinforcing the concepts.

por Maxwell N M

7 de abr. de 2016

Lasso is very cool for dimension reduction i discover another algorithm powerfull than Personal Component Analysis

por Jim J

1 de nov. de 2018

Great course and well explained. Need to invest time if you want to rally get benefit out of the content covered.

por Chokdee S

15 de abr. de 2017

This is one of my favorite courses for ML, The best course for learning regression stuffs ever. I really love it.

por kripa s

25 de mar. de 2019

I must say it was great learning experiance. Everything releted to ML regression has been covered so eloquently.

por Marcus C

8 de feb. de 2016

great in depth course on regression. I really enjoyed the implementations of different algorithms all by myself.

por Mr. J

9 de ene. de 2020

I am giving 5 stars. Visualization of regularization is illuminating. The programming assignments are useful.

por Sushil B

8 de sep. de 2016

Well organised. In depth optional lectures help you learn more about the theoretical foundations. Recommended.

por Gilles D

1 de jun. de 2016

Very good course, will teach you a lot about regression and it will become second nature doing it on your own.

por Ashutosh A

9 de feb. de 2016

Nice illustrations and concepts are explained in clear & concise way through real life examples and data sets.

por Xiaohua X

2 de feb. de 2016

This course covers a lot of ground. It not only has hands on practices but also explains the algorithm behind.

por siddhesh m

29 de may. de 2022

Really great course, the the deatils and intuation learned by this course is really asmezing. Thansk a lot.

por SATYAM C

27 de jun. de 2018

ever best for regression. even better than Andrew NG. Detailed Mathematics explanation is part of this course

por Jay Y

20 de ago. de 2021

Thank you. Very engaging course, and excellent teachings of inner workings of the various regression models.

por NAKKA V S B

22 de sep. de 2016

Very good course on Regression but statistical inferences could have been added to give a completion feeling

por Yuan L

8 de ago. de 2017

A great course covering most of the fundamental concepts and techniques! Very detailed and well explained!

por Aliaksandr K

28 de ene. de 2017

It's really practical course which covers a lot of main regression concepts and great teachers. Thank you!

por Amlan D

25 de mar. de 2016

Nice intro to regression! Shorter lectures and more programming challenges would have made it even better.

por Kunal B

2 de jun. de 2016

This course is awesome. It stimulated my interest throughout the course. Course Material was very useful.

por Frank L

2 de jul. de 2017

Great Course! Very well explicated and clear. It's a good start for the beginners and not so beginners.

por Regis G

31 de mar. de 2017

I learnt a lot during this course. The content was very well delivered, and the labs were very helpful.

por Giovanni B

25 de dic. de 2015

I think this course is great, Emily and Carlos explain things so clearly and provide excellent material

por יונתן ה

27 de nov. de 2021

Great course. Good assignments - python implementations, different than the known Stanford's ML course

por Alexis C

9 de may. de 2016

very intuitive explanations. learned a lot, despite having taken many machine learning classes before.

por Tripat S

10 de ene. de 2016

This is the best course in ML...Prof Carlos and Prof Fox are the best ....Would recommend for evryone