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學生對 华盛顿大学 提供的 Machine Learning: Regression 的評價和反饋

4.8
5,462 個評分
1,014 條評論

課程概述

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....

熱門審閱

PD

2016年3月16日

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

2020年5月4日

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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126 - Machine Learning: Regression 的 150 個評論(共 981 個)

創建者 Mohamed A

2016年5月1日

Great course! all materials are well structured and introduce each concept concisely. I enjoyed all programming assignments. Take this course if you would like to know more about regression rather than simply finding the perfect hyper-plane that approximate your data.

創建者 Victor C

2017年5月28日

Emily Fox is exceptional. It's a smooth airplane ride through often turbulent paths. That's harder to do than it might seem as most teachers get mired in details that confuse and/or distract the student. I would think that any course she teaches is worth taking.

創建者 Abhinav U

2016年1月11日

Great course, very detailed and hands on, also including appropriate amount of mathematical rigour to help you understand what is going on under the hood. Highly recommended. I specially liked the modules on Ridge regression and Lasso regression, really well done.

創建者 Dan L

2015年12月28日

I found this an excellent introduction to the topic with a good mix of well-presented material and practical application using the IPython notebooks. I would love to have the course finish with a project where we apply the learned methods to a different data set.

創建者 张明

2015年12月4日

Very responsible teachers and practical classes content.You can not only learning the ML theory from scratch,but also learn to implement the algorithm using python by yourself.This is the best ML course I ever seen.

Thanks for the teachers' hard-work.You are great!

創建者 Muhammad U C

2016年2月11日

Excellent. This is an ideal course in order to understand various aspects of regression techniques. Explanation using hands-on exercises helps me learn this course very effectively. I must appreciate the efforts of both Instructors (Prof. Emily & Prof. Carlos).

創建者 Amal G

2016年9月10日

I felt that the course was detailed and contained significant in-depth study about regression techniques. The assignments were well designed, starting from a single step and eventually enabling the candidate to be able to write the complete methods on his own.

創建者 Lech G

2016年1月5日

This is probably the best Coursera course I have completed so far (and I am kind of Coursera junkie). very well structured, the right amount of math and driven by the experiments on the real data.

Looking forward to Classification course and others in series.

創建者 Fan D

2017年1月3日

The regression is done very well. I love the tutorials especially, they are very clear with good test feedbacks on some of the latter week contents. If you want to get into machine learning, this is a very important part to help you with all the other parts.

創建者 Igor P

2016年2月26日

I liked pretty much all of the content.

The lectures are detailed.

The assignments helped me understand the techniques used in regression. The step by step approach is great.

What I dislike a bit is the promotion of proprietary and expensive Graphlab software.

創建者 Cal D

2015年12月19日

A few minor glitches with the homework assignments so far. Hopefully this is only because it is the first time the class is being offered.

I love the instructors. Great enthusiasm and both clearly love what they do. Inspiring for data scientists in training.

創建者 SIMING D

2018年7月8日

This is a great course! The course is easily understand, the lecturers are very nicely talking in the videos to show you the knowledge of regression. The assignments are designed in a way helping you learn, practice and implement the regression algorithms.

創建者 Jerry S

2017年4月2日

Really exciting course. The concepts are well explained and implementing algorithms by myself is really a inspiring experience. It is really a pity that the last 2 courses in the specialization were canceled. I am even willing to pay them for 100$ each!!!!

創建者 Christopher W

2016年3月28日

Pretty challenging from a mathematical perspective, but extremely interesting and well-explained. I was glad to see there were plenty of opportunities to use Pandas and other Python libraries instead of just relying on Graphlab. Very happy with this class.

創建者 Aviad B

2017年10月10日

Excellent course. Highly recommended. Emily Fox is clear and comprehensive. In addition, this module's exercises can be fully completed using Python's Pandas sklearn and numpy libraries and without requiring the propriety GraphLab library. Good work!

創建者 Dauren

2017年12月23日

Good insight into regression models. You will dive into the details of implementations of Lasso and Ridge regularization techniques. The course is actually easy to grasp for graduates with technical background, never the less gives good knowledge.

創建者 Adil A

2017年3月15日

Very nice course... The instructors were really great, the explanations, the presentations, even the color schemes were all really great... Definitely one of the most fun courses I've taken at Coursera... The assignments were also well designed...

創建者 Filipe G

2016年3月12日

The best Machine learning course I ever took. I compare it very favourably to Jeff Leek's course, or Andew Ng's course - which are both good in their own right.

A lot of effort went into making this a really good course. I very much recommend it.

創建者 Fernando M P

2017年10月8日

An incredibly good approach to regression. It is the perfect continuation of the introduction course, it provides very good skills to solve regression problems. I´m eager to start with the third course of the specialization after this one!

創建者 Ruan P R T

2016年4月30日

All concepts are explained really well! Knowing all the mathematics behind machine learning can never hurt, but when it comes down to actually implementing something useful it all boils down to the practicalities of the implementation.

創建者 Manoj K

2016年2月8日

Wow.... to complete this course, one really needs to work hard... one of the best teachers and the way they build concepts, so easy and systematic... thanks you so much for making me learn some of the challenging concepts with ease...

創建者 Sundar J D

2016年2月7日

Great course and great instructor. Course covers regression models in great detail. The instructor's explanation of concepts and intuition behind why things are the way they are was really helpful to learn and appreciate the concepts.

創建者 Erik R

2017年5月23日

A really nice course, explanations in the videos are absolutely clear. I do have to say, however, that I was hoping to go into kernel-based regression a bit further. But overall, a great course which i definitely recommend to others!

創建者 Brian B

2016年1月11日

One of the top Coursera courses I've had the pleasure of taking!

The instructors do a great job of making the math understandable (although I am a graduate student in applied math, so the mathy parts of machine learning aren't new).

創建者 Nitin K M

2019年9月12日

Highly recommend this course if anyone wants to truly understand the stats used behind regression. Professor Emily has taught this specialization in the best way possible. Thank you Cousera for providing such specialization online.