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Tensorflow similarity study notes 5 2021SC@SDUSC Learning content: Tensorflow concept summary and learning feature extraction Any of the steps in the previous operation: Different image sizes; There are 62 tags or target values (because your tags start at 0 and end at 61); The distribution of traffic sign values is very uneven; There is vir ...

Machine learning project (I): survival probability analysis of Titanic passengers Project background: In 1912, the Titanic, then the world's largest passenger ship with the most luxurious internal facilities, with the reputation of "unsinkable", hit an iceberg and sank 3700 meters below the bottom of the Atlantic Ocean during he ...

1.Matplotlib Library 1.1Matplotlib features matplotlib is the most commonly used drawing module in pythonThe Pyplot sub module of matplotlib is very similar to MATLAB. It can easily draw various common statistical graphics. It is an important graphic tool for users to conduct exploratory data analysisYou can set the graph title, line style, c ...

Reference link: https://blog.csdn.net/u013733326/article/details/79702148 Prepare package We need to prepare some software packages: numpy: it is a basic software package for scientific computing in Python.sklearn: a simple and efficient tool for data mining and data analysis.matplotlib: is a library for drawing charts in Python.testCases: s ...

1, Introduction to SVM General framework of machine learning: Training set = > extract feature vector = > combine with certain algorithms (classifiers: such as decision tree and KNN) = > get the result 1 SVM definition support vector machines (SVM) is a binary classification model. It maps the feature vector of an instance to some poi ...

preface Taking CSDN as a learning note has no commercial use. I hope to communicate with you and make progress together. Learning materials are from Github: link Modules and functions Functions referenced in Github source program from numpy import * import operator Text file processing Helen appointment text file datingTestSet2.txt Becau ...

I introduce Anomaly detection (Anomaly detection) is one of the most mature applications of time series data analysis. It is defined as the process of identifying abnormal events or behaviors from normal time series. Effective anomaly detection is widely used in many real-world areas, such as quantitative transactions, network security testing ...

Bayesian theory Continuous and discrete feature processing Naive Bayes classifier Semi naive Bayesian classifier Bayesian theory In our study of probability theory, Bayesian theory is basically implied everywhere. Bayesian theory is simply a method of probability transformation, which transforms a difficult correlation probability into ...

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day4 - classification problems (understanding and sharing of relevant case codes) experience On the fourth day of team study, datawhale, an open source learning organization, used sklearn to build a complete classification project, reviewed some classification models in machine learning, practiced the calling codes of relevant models, ...