Voltar para Machine Learning: Regression

4.8

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5,080 classificações

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956 avaliações

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....

KM

May 05, 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

Mar 17, 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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por Ian F

•Jun 09, 2017

Great course - you'll become much more accustomed to Python if you aren't already (I'm an R convert) and really learn the principles behind regression analysis.

por Kris D

•Dec 24, 2016

Covered a lot of the common practical aspects of regression modelling and also covered the calculus derivations for those who are curious. Great course overall.

por Hongbing K

•Jan 02, 2016

Very clear and thorough explanation on regression and implementation details. The closed-form calculation and comparison against gradient descent is excellent.

por Emil K

•Jan 14, 2020

I love how this course goes deep into the math, yet makes it quite approachable even if you have no math skills. Emily is so good at explaining the concepts!

por Bruno V R S

•Aug 27, 2020

Excelent Course. It not only teaches the ideia behind the topics but it also provides an in-depth view of the algorithms and its parts. Totally recomend it.

por Salomon D

•Aug 28, 2018

Great background through applications of linear regression and explanations that are step by step that allow the understanding and construction of learning.

por Marcus V M d S

•Oct 07, 2017

Thank you for all the effort you put in the exercises and the data. It was a great course! Perhaps you could put references for further study of the topics?

por Melwin J

•Jul 30, 2017

The best course on regression I have attended so far !!! I really liked the way professor explained the concepts. Has resources on in-depth details as well.

por Mantraraj D

•May 05, 2018

The course should move away from the default graphlab implementation to scikit-learn as the package is outdated and python 2 is about to go out of support

por girish s

•Dec 19, 2015

Liked this course, really good assignments which help you to master the concepts thought in the lectures. Thanks a lot for making this available for us.

por Tarun G

•Jul 22, 2017

One of the best courses on Regression. Covers topics in detail with all basics covered. Highly recommended for all analysts/data-scientists out there.

por Dennis M

•Apr 25, 2016

This is a great course, pretty obvious that Emily 1) knows her stuff and 2) put a lot of work into this class to provide an a nice look at regression.

por Santosh K D

•Jun 05, 2019

Professor Emily Fox should do a follow up for this course. It was so simple and intuitive to understand. I want to work as a PhD student under her.

por Zhao Y

•Feb 27, 2016

Excellent instructor!

The concepts, though hard, are well explained in a clear and organized manner.

The assignments are very practical and helper.

por Bernardo N

•Jan 16, 2016

Best Regression MOCC available online! Also consider the whole Machine Learning specialization, one of the best series you can find on this subject

por Mark W

•Aug 12, 2017

Excellent course. Emily and Carlos are fantastic teachers and have clearly put in a huge amount of effort in makign a great course. Thanks guys!

por Saransh A

•Oct 12, 2016

This is probably the best course on Regression for ML out there

And this specialisation is probably the best! for Basic Machine Learning... KUDOS!

por Bhavesh G

•Apr 03, 2020

I learned lot many things during this course like simple regression, calculate RSS, gradient descent, feature selection and k-nearest neighbour.

por Anirudh N

•Jan 09, 2017

Very well organized course. After taking this course I am able to work on practical problems that can be solved using regression. Thanks Emily!

por vishnu v

•Jan 03, 2016

Great course on regression. Covers almost all aspects on how to build a regression model from scratch, also covers few advanced topics aswell.

por Jane T

•Jun 30, 2017

Difficult material, but the style of the lectures and assignments managed to keep it fun and interesting, all the way to the end. Amazing job

por 戴维

•Mar 06, 2016

It is an excellent course, which can not only equip you with tools but also allow you to know the underlying reason. And it is interesting.

por Leandro R

•May 12, 2018

This course is very good. It went above my expectations. The instructors are great and I learned a lot of Python here. I really recommend.

por Nicolas P L

•Jul 13, 2020

Great Course, it focused both in the theory and practical approaches in a challenging way such that you could learn better the concepts.

por Yashaswi P

•Sep 13, 2018

The only hindrance I had is with understanding the problem statements in assignments. It would be better to use a more unambiguous text.

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