你是否好奇数据可以告诉你什么？你是否想在关于机器学习促进商业的核心方式上有深层次的理解？你是否想能同专家们讨论关于回归，分类，深度学习以及推荐系统的一切？在这门课上，你将会通过一系列实际案例学习来获取实践经历。在这门课结束的时候，

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你是否好奇数据可以告诉你什么？你是否想在关于机器学习促进商业的核心方式上有深层次的理解？你是否想能同专家们讨论关于回归，分类，深度学习以及推荐系统的一切？在这门课上，你将会通过一系列实际案例学习来获取实践经历。在这门课结束的时候，

Python Programming, Machine Learning Concepts, Machine Learning, Deep Learning

4.6（8,582 个评分）

- 5 stars6,254 ratings
- 4 stars1,834 ratings
- 3 stars322 ratings
- 2 stars84 ratings
- 1 star88 ratings

Sep 28, 2015

Excellent course, with really good lectures, material and assignment. Plus the professors are really amazing and their enthusiasm is really refreshing and makes the class more interesting. Loved it!

Jun 05, 2017

This course is very helpful for people who are novice in machine learning. The course uses Graphlab Create which is different from scikit or R-libraries, but the tool(Graphlab) is excellent to use.

从本节课中

Regression: Predicting House Prices

This week you will build your first intelligent application that makes predictions from data.<p>We will explore this idea within the context of our first case study, predicting house prices, where you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). <p>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.</p>You will also examine how to analyze the performance of your predictive model and implement regression in practice using an iPython notebook.

#### Carlos Guestrin

Amazon Professor of Machine Learning#### Emily Fox

Amazon Professor of Machine Learning

[MUSIC]

In fact, we can actually look at the coefficients with that line for our model.

So we can take this square foot model that we built and we can call the function get.

And we can get the coefficients.

So these are what in the chorus we call the weights.

And so, there are two weights, two coefficients.

The first one is the intercept to where this line crosses the y axis.

In this case, -$44,000.

And the second one is the coefficient of the square feet, so this angle,

which corresponds to, if you interpret it in this case, the price per square feet.

How much does a square foot of a house cost?

500 a square foot, how much it adds.

And its $280 per square foot.

This is the kind of average for Seattle.

Some houses cost more per square foot, the ones up here.

Some houses cost less.

But on the average, if you think about it, it's about $208 per square foot, or

at least according to this regression model.

[MUSIC]