Data Science Linear Regression

The author of this article: Wuyuchuan &http://www.aliyun.com/zixun/aggregation/37954.html ">nbsp; The following is my experience in the past three years to do all kinds of measurement and statistical analysis of the deepest feelings, or can be helpful to everyone. Of course, it is not ABC's tutorial, nor detailed data analysis method introduction, it is only "summary" and "experience." Because what I have done is very miscellaneous, I do not learn statistics, mathematics out ...

Machine learning is a combination of art and science. No machine learning algorithm can solve all the problems. There are several factors that can influence your decision to choose a machine learning algorithm.

Machine learning is a science of artificial intelligence that can be studied by computer algorithms that are automatically improved by experience. Machine learning is a multidisciplinary field that involves computers, informatics, mathematics, statistics, neuroscience, and more.

There are many articles on machine learning algorithms that detail the related algorithms, it is still very difficult to make the most appropriate choices.

Data mining, which mainly solves four kinds of problems, is a very clear definition of several kinds of problems that it can solve. This is a high degree of induction, and the application of data mining is a process to deduce these types of problems. So let's look at how the four types of problems it solves are defined: 1, classification problem classification problem is a predictive problem, but it is different from the general prediction problem, but the difference is that the results of its predictions are categories (such as a, B, C three) rather than a specific value (such as 55, 65, 75 ...). ...)。 ...

Today, I will share all the questions I encountered during the interview and share how to answer them. Some of these questions are relatively normal and have a certain theoretical background, but some are very innovative.

The following small series summarizes 10 best data mining tools for everyone, which can help you analyze big data from various angles and make correct business decisions through data.

Introduction 1988, I study in mathematics department of Zhejiang University, Professor Van Dayin "Probability theory". I once asked her: "The proportion of women and men in newborn births nationwide is 51.2:48.8." If the statistical results of the provinces are the same, do they contain more information? "Teacher Fei said:" If the same probability occurs, the results of the provinces have no more information. 　　"More than 20 years later, I realized: In theory, teacher Fei's answer is completely correct, but in reality, the amount of information is not the same." Big Data is a popular word and has received widespread attention from the world's industry. An old academician once said: Big Data Master ...

As the key word in the IT field, the "Big Data" is always in the spotlight, and the analysis and utilization of it has attracted much attention. On the other hand, problems that cannot be solved by IT technology, existing organization and talent skills are gradually surfacing. This requires "the analysis of data and its integration with the business technology." This paper summarizes the technologies needed to apply data analysis to the business and how to implement effective information applications in the enterprise. At the same time, it also lists the advanced examples of Japan and abroad. Three major technologies below, let's take a look at the big data age of the technology companies need? Business Skills This ...

This article will introduce some practical examples using IPython and pandas for investment analysis and http://www.aliyun.com/zixun/aggregation/10341.html "> Statistical analysis." Let's do a common analysis and you may be able to do it yourself. If you want to analyze stock performance, you can: find a stock in the Yahoo financial zone. Download historical data and save it in CSV file format. Will be CSV ...