[Conclusion]-2018 w1, summary-2018w1
I don't want to sum up 2017. Let's go over the past, but I have gained a lot in 2017. 2018 the most important thing is to make money because you want to buy milk powder. Two brushes are needed to make money. Therefore, the goal of 2018 is to learn Data Analysis and machine learning. I hope I can do something in these two fields. To accomplish this small goal, the goal is divided into several steps.
- Data cleansing
- Data Conversion
- Data Extraction/data preprocessing
- Data analysis/Machine Learning
The implementation of each step is to read as many blogs and related books as possible. If the students who are studying, those who are engaged in other work, or Daniel has recommended blogs or books, please leave a message for a few minutes. The implementation method is planned to take some time every day to complete a certain amount of learning.
WeeklyI have posted blogs I have learned or used to accomplish my goals in zhihu and the blog community. I hope you can help me identify errors and mistakes.
Start every weekI am able to make a summary and review of the content of this week, and send it to zhihu and the blog Park again to study together. At the same time, I also hope that you can help me to point out errors and misoperations. In the first week of the first day of the second day, we will learn about data cleansing in this week, this week's blog includes the following content: 2018 w1 blog list.
- [Data cleansing]-chaotic zip code data
- [Data cleansing]-clean "dirty" data in Pandas (1)
- [Data cleansing]-clean "dirty" data in Pandas (2)
- [Data cleansing]-cleaning "dirty" data by Pandas (III)
- [Data cleansing]-numbers that look the same
