Machine Learning Algorithm Competition Actual Combat--1, the first competition

Table of contents

 Competition process:

1, 

2,

thinking exercise

The reason why it is strongly recommended to use competitions as an important way of active learning is because it is really an excellent way to quickly get started and active learning. For beginners, their level is not enough to support them to directly enter the enterprise to contact the actual The application scenarios, and the knowledge gained from the book is a bit superficial after all.

Under the torrent of the times, all walks of life are looking for a way to survive. It is a good way to use advanced technology to complete the transformation. Some companies have begun to seek the help of artificial intelligence and began to solicit excellent algorithm solutions from the society. In addition , Researchers in the academic field are also eager to obtain enterprise scenarios and data for algorithm research, which has given rise to various competition platforms. For beginners who are interested in entering the field of machine learning for research or related work, the competition is a very cost-effective practical choice. It can be said that there is no threshold, and anyone can participate.

The following article contains almost all artificial intelligence & machine learning competitions: Machine Learning & Artificial Intelligence Competition Compilation - Zhihu (zhihu.com) icon-default.png?t=MBR7https://zhuanlan.zhihu.com/p/99078649

 Competition process:

1, 


When participating in the competition, the first thing a contestant should do is to be familiar with the topic and the data, which often contain a lot of important details.
Understanding the topic is always the first and most important step. Accurately understanding the meaning of the topic can avoid We take a lot of detours in the problem modeling of active learning. Not all data is a form of feature labeling that can be directly added to model training. In many cases, it is necessary to analyze the data and then abstract the modeling goals and solutions.
 

2,

 

Thinking exercise:

 It's relatively simple, and everyone can do it by themselves.

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Origin blog.csdn.net/m0_63309778/article/details/128800577