Tag：data mining
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Time：2020-1-9
As a hot word in recent years, artificial intelligence has always been a powerful force in the scientific and technological circle. With the iteration of smart hardware, smart home products have gradually entered thousands of households, and AI related technologies such as voice recognition and image recognition have also experienced stepped development. How to treat […]
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Time：2019-12-10
Now there are many friends who are interested in big data industry, but they don’t know how to start. What books should you read as a beginner of zero basic big data? Today, I did some sorting as a reference, hoping to help those students who are interested in big data. 1. Big Data Engineer […]
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Time：2019-11-18
One hot coding is necessary in feature processing, which is how we apply it in projects, #Sklearn usage from sklearn import preprocessing enc = OneHotEncoder(sparse = False) ans = enc.fit_transform([[0, 0, 3], [1, 1, 0], [0, 2, 1], [1, 0, 2]]) The principle of analysis can be referred to: linkThe core logic of onehot coding […]
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Time：2019-10-28
Process and method of data mining 1. task: association analysis cluster analysis Classification analysis Anomaly analysis Specific group analysis Evolution analysis 2. method: Statistics On line processing analysis information retrieval machine learning classification Practical application: application classification / trend prediction / recommendation of related products regression analysis Practical application: forecast sales trend clustering Practical application: […]
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Time：2019-10-7
This article belongs to forwarding, on the basis of this article, I will add some of my own ideas in the future. I recently looked at schools abroad, separating machine learning from data mining. Data mining mainly deals with databases, learning what data warehouses, and using Oracle software. Machine learning seems to be closer to […]
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Time：2019-10-6
Preface This course is very suitable for beginners. It is much simpler than Ng’s open course at Stanford University. It has less mathematics and more compact content. It covers a wide range of contents. It aims to build a bridge between beginners and machine learning. It is worth mentioning that this course is closer to […]
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Time：2019-10-5
This chapter is more dry goods, looks more tired, the harvest is also relatively large.Keep reading and writing.It’s very tiring to write formulas. I hope segmentfault can support latex formulas as soon as possible.We have been unable to grasp the optimization of this thing, both theory and practice are deficient, and strive to win this […]
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Time：2019-10-4
General method of $2.2 Subgradient method Converting to Common LP, SDP Problems This general method does not mine the structure of the 1 norm problem itself, so the convergence rate is slow.LP, SDP and other methods are too pursuit of optimization accuracy, which is not important in the field of machine learning. It is important […]
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Time：2019-10-3
Finally, we can input the formula directly. I hope SF will get better and better. At present, the rendering speed of formulas is a little slow, and the formula rendering is also problematic. (Block) Coordinate Descent Alorithm The so-called (B) CD means that at each iteration, not all parameters are optimized, but only one parameter […]
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Time：2019-10-2
I looked up a lot of information about this problem, meaning that CSV read nine attribute (feature / dimension) values, but read only one, and the third line has a problem.Then there are all kinds of formatting spaces in the data, and so on. In fact, there is nothing wrong with setting up the attribute […]
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Time：2019-10-2
Data science is OSEMN (with the same pronunciation as awesome), which includes Obtaining, Scrubbing, Exploring, Modeling, and iNterpreting data. As a data scientist, I spend a very long time on the command line, especially when it comes to acquiring, collating and exploring data. And I’m not the only one to do that. Recently, Greg Reda […]
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Time：2019-10-1
LibShortText is an open source Python short text categorization toolkit (including headings, text messages, questions, sentences, etc.). On the basis of LibLinear, it further optimizes short text. Its main features are as follows:– Support multi-classification– Input text directly without preprocessing of feature Vectorization– Bigram, no pause, no part-of-speech filtering– based on linear kernel SVM classifier […]
