Machine Learning: Regression(으)로 돌아가기

4.8

별점

4,932개의 평가

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927개의 리뷰

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....

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

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!

필터링 기준:

교육 기관: Omar N T

•Mar 30, 2016

it gave more details than my class room. it also adopts a practical approach to learn. it is a great course in regression especially for practitioners.

Thanks Carlos and Emily :)

교육 기관: Dipankar N

•Dec 11, 2017

Great course on Regression. This will help build basic for upcoming modules. Emily teaches the concepts in a simple way. I liked the structure and coverage of Regression topic.

교육 기관: Nadya O

•May 06, 2017

Great material, this was tougher than the previous course. It is challenging and more exercises to practice which help to a better understanding of the concepts. Great mentors!

교육 기관: Rahul J

•Apr 03, 2017

An extremely well designed course, I am an instructional designer myself, so adding weight to the words. Would have appreciated a few more assignments for the last week though.

교육 기관: Chengcheng L

•Dec 28, 2015

I feel I understand regression models better than before. But I still need to read more books on the same topic to actually convert what I learned here to long term memory :)

교육 기관: Lavaneesh S

•Sep 17, 2019

Fantastic Course, allowed me to gain insights to regression. Both the instructors like always have been excellent. Shout out to coursera for allowing me to take this course!

교육 기관: 陈哲鸿

•May 19, 2018

It's a really nice course.What i've learned in this course: how to implement a regression model through my own hands, assessing performance, feature selection...and so on.

교육 기관: clara c

•May 13, 2016

This course is very well organized and all the information is relevant. Everything is explained in great detail. The exercises really make you feel that you are learning.

교육 기관: Do H L

•Jan 14, 2016

All the courses in this specializations are very well-made and rigorous. I think all MOOCs, especially techinical ones, should be as well-designed as this or even more.

교육 기관: Fahim K

•Jan 06, 2016

The course is really helpful. It has started with simple Regression model and gradually build the different advance regression model. Thanks for this wonderful course.

교육 기관: Aditya K

•Aug 15, 2016

rigorously explained some of the most important algorithms in regression world, also the pros and cons of using certain algorithm for certain conditions. totally worth

교육 기관: Sahil D

•May 16, 2016

Good overall theoretical and practical explanation of the material, I was also able to use scikit learn and pandas without any difficulties instead of graphlab create.

교육 기관: isanco

•Jan 25, 2016

Great class (really liked the graphical interpretations of Lasso and Ridge optimizations).

Perhaps some quizzes (and especially assignements) could be more challenging?

교육 기관: Iñaki D R

•Jul 12, 2020

Great course, excelent professors & simple yet accurate explanations, always guiding you through the course and through practical implementation of acquired knowledge

교육 기관: Thomas K A W

•Jan 08, 2018

Great course! I love the instructors and the thoroughly designed structure of their course. The effort they put into this course certainly shines through every video!

교육 기관: Jessie J S

•May 12, 2018

I love this course! It explains more about Regression itself and not just discussing on how to use libraries for it! Very intuitive and informative at the same time!

교육 기관: Kapil K

•Feb 14, 2017

its a great course. little bit disappointed from the decision of not continuing Recommended systems and capstone project. PLEASEEEEEE roll out course 5 and 6 as well

교육 기관: Saheed S

•Sep 19, 2017

Nice course. I started with this specialization as a beginner. I was very intuitive and great course I would recommend to others people interested in data science.

교육 기관: Santosh G

•Jun 10, 2016

The Regression course is pretty amazing. Got to learn a lot of cool stuffs. Emily Fox made everything clear. Glad to have taken this course and the specialization.

교육 기관: Hritik K S

•Oct 27, 2019

Coursera is shaping me in the best version of myself through knowledge and guide. I am always be grateful of god that I found Coursera. My online teaching guru!

교육 기관: 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.

교육 기관: 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.

교육 기관: 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.

교육 기관: 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!

교육 기관: 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.