Chevron Left
Voltar para Machine Learning: Regression

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

5,328 classificações
994 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

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!

4 de Mai de 2020

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

Filtrar por:

176 — 200 de 961 Avaliações para o Machine Learning: Regression

por Fede R

2 de Jan de 2017

This course is great. Things are very clearly explained. I am particularly happy because it helped me to understand many mathematical concepts. I will try not to be scared about formulas anymore.

por Aynalem M

26 de Abr de 2020

Very informative, practical course with excellent instructors, I would recommend this course to anyone doing basic machine learning. The only issue I see is that the course can be offered in R.

por Chia-Sheng L

4 de Jan de 2016

This course offer many aspects like graphic comparison or detail math explanation help us understand more easily what a model or method means. The teacher have great effort on material design.

por Carlos S M L

22 de Ago de 2020

Un excelente curso que nos introduce a este interesante tema de la regresión. Demasiado útil y explícito a la hora de abordar los temas, realmente fue una gran experiencia. Super recomendado.

por Anuj S

28 de Abr de 2020

One of the best course on Coursera to learn about Regression with great explanations in mathematics as well as programming. Great analogy used which helps in learning much faster and longer.

por Prashant M

30 de Set de 2017

This was a very satisying course with the intensity and queries that challenge me and wish to learn more. I am quite excited to learn more with the new ML bug that has caught me! Liberating.

por Wenxin X

12 de Mar de 2016

Learned a lot! Now I have been acquired a basic understanding of machine learning! Materials are not much, so it's not painful to accept. Recommended for everybody interested in this topic!

por Gustavo K A

8 de Jan de 2016

I had the clear sense of actually learning and not just "copying & pasting" bits of code. The questions and problems are challenging enough to make you stop and think about you just learned.

por Sergey M

19 de Jan de 2016

A very good course! Especially that scikit-learn can be used as framework for solving assignments and at the same time exercises for programming of learning algorithms from scratch. Thanks!

por Bilkan E

16 de Out de 2016

Incredible course!

Very good, intuitive and simple introduction to general use machine learning and optimization techniques. I am already employing techniques learned here to my daily work.

por vivek s

31 de Ago de 2016

it's a nice course. I have learnt many new concepts. I am from information systems background and want my career towards data science. This course helped me a lot in learning new concepts.

por Sekhar K

2 de Abr de 2017

This course is phenomenal! I am learning a great deal. Dr. Emily Cox is fantastic with her slides, explanation and the way she (and Dr. Carlos Guestrin) structured the course. Loving it!

por Ling Z

8 de Abr de 2019

I took this class long time ago and just revisited it today. Compared to other online class, this class has a lot details. I am satisfied with both the clarity and depth of the content.

por Fabio P

3 de Abr de 2016

I really like the learning approach in this course: at first you learn how to use the algorithm and after that you learn how to implement it yourself. That way it's never disappointing.

por George P

16 de Mai de 2017

Straight to the point and with useful material to check back whenever you feel is necessary. Learning but also good annotated notes in order to revise things later are very important.

por Zachary C

29 de Abr de 2017

the professor does an excellent job explain the subject thoroughly, including good in depth descriptions of matrix algebra and how it applies to things like multi-variable regression.

por Alexander T

30 de Dez de 2015

A very comprehensive course that covers not only regression, but all base Machine Learning concept. Thanks to Emily, she explains rather complicated topics in a clear and concise way.

por Ben K

22 de Fev de 2016

Lasso, l2 regularization, ridge regression, etc. - appropriate level of technical detail, first principles discussion, etc. means that a lot of good info was packed into this course.

por Val V

8 de Dez de 2020

Excellent introduction to linear regression by top-notch instructors. The description promised it would be action-packed - and it was! Now I can't wait to move on to Classification.

por Vibhutesh K S

20 de Mai de 2019

This is indeed a good course. Covering even much more than I had previously expected. The instructions were quite clear to me and the programming assignments were quite interesting.

por Nitish V

25 de Set de 2017

The course is really good for people planning to step into machine learning field. Not so deep , but covers all the relevant topics. Thanks to instructor for making it look so easy.

por Alfredo A M S

26 de Jun de 2016

Started a little slow, and it may seem repetitive if you see all videos from one week in one day, otherwise I feel it has a good pace.The content was interesting and well explained.

por Borna J

19 de Jun de 2016

I love everything about this course. the course material is easy to follow. I also like the coding exercises. I highly recommend the specialisation so far (this is my second course)

por Girish N

6 de Ago de 2020

The instructors take care to teach every concept as precisely and intuitively as possible. The assignments are challenging and make sure you learn and internalize the concepts well

por Charlotte B

24 de Jul de 2019

I definitely learned a lot in this class about different techniques and ways to use regression in machine learning. I also feel like I learned a lot about how to program in Python.