项目详见：

https://github.com/ahomer/airbnb_bst

Business and Data Understanding

As talk on Airbnb kaggle data website, the following Airbnb activity is included in this Boston dataset:

• Calendar, including listing id and the price and availability for that day
• Listings, including full descriptions and average review score
• Reviews, including unique id for each reviewer and detailed comments

Let us take a look on these three csv files.

Calendar

It shows that the hosts are not avaible everyday and price may be changed at the busiest seasons.

• What is the most expensive season in Boston?
• Which hosts are the most favorite？

Listings

Summary information on listing in Boston.It contains location, host information, cleaning and guest fees, amenities and so on.
We may find some import factors on price.

• What are the top factors strong relation to price?
• How to predict price？

Reviews

We can find many interesting opinions,sush as

• What are the most attractive facilities? It is big bed, large room or location?
• What will lead to bad impression？

Data preparing

Clean Calendar

• So we can see the most expensive season is from August to November，especial September and October.

• You can get a lowest price if you go to Boston at February.

• The most expensive listing_id is 447826.Go to Boston and experience one night.

Clean Listings

Let us calculate the mean/std of 'Price'.

• Assuming that prices obey normal distribution
• The price should be between mean-2std~mean+2std

Clean Reviews

Review the reviews.csv file,you will find there are different languages.We just need to keep the english comment.
We need a lib 'langdetect'.

Modeling and evaluation

Let's try to predict the price based on the columns in the listing we selected.

• What are the top factors strong relation to price?

Top 6 factors strong relation to price:

• bedrooms
• room type : Private room
• number of reviews
• accommodates
• bathrooms
• review scores rating

Deployment

Mostly,the model will be deplyed on product environment based on a RPC server or http server.
You can deploy the model with Tornado(python web framework).

All other answers were helpful, but can be other scenarios too, follow here as per yours. Mine was ubuntu 1604, so use following:-

ubuntu1604 config --default-user

if you installed ubuntu 1804:-

ubuntu1804 config --default-user

if you used default one, then:-

ubuntu config --default-user

之所以登录：google 了一下午找到答案。 安装的是ubuntu1604版本，网上使用的“ubuntu config --default-user ”运行一直报错如下：

“
ubuntu : 无法将“ubuntu”项识别为 cmdlet、函数、脚本文件或可运行程序的名称。请检查名称的拼写，如果包括路径，请确保路径
正确，然后再试一次。
所在位置 行:1 字符: 1
+ ubuntu config --default-user
+ ~~~~~~
+ CategoryInfo : ObjectNotFound: (ubuntu:String) [], CommandNotFoundException
+ FullyQualifiedErrorId : CommandNotFoundException”

终于找到正确答案。

原因：
ubuntu安装时会提示设置用户名和密码，这样root的密码就是随机的。需要将root用户设置为默认账户，并设置密码后 才可以正常使用su和sudo。

• 如何查看ubuntu 子系统的账户和密码？

账户和密码保存在%userprofile%\AppData\Local\Packages\CanonicalGroupLimited.Ubuntu16.04onWindows_79rhkp1fndgsc\LocalState\rootfs\etc 文件下 shadow 和shadow- 文件中。