Programming VIP

1, ForewordIt refers to the division of similar data together. The specific division does not care about this kind of label. The goal is to aggregate similar data together. Clustering is an unsupervised learning method.2, General process of clusteringData preparation: feature standardization and dimensionality reductionFeature selection: select ...

preface    through seven articles, we give you a general introduction to the production process of data visualization, Of course, this project is also written by Eric Matthes "Python programming from introduction to practice" is a project in the book. However, I introduce this project to you through certain features and thr ...

Good morning, everyone. My surname is Wu. If you think the article is OK, you can also call me Miss Wu. Welcome to the world of data analysis and study with me! Interested friends can pay attention to me Data analysis column , there are many high-quality articles to share with you. The first method from openpyxl import load_workbook wo ...

catalogue First, Simulated annealing algorithm (SA). 1. Basic theory of SA 2.SA solves the maximum value of the function 3.SA toolbox 2, Genetic algorithm (GA) 1. Theoretical basis of GA 2.GA solves the maximum value of function 3.GA toolbox 3, Particle swarm optimization (PSO) 1. Knowledge of PSO algorithm 2.PSO algorithm design 3. ...

Case 1 (happiness prediction) Background introduction Happiness involves philosophy, psychology, sociology, economics and other disciplines. At the same time, it is closely related to everyone's life. Everyone has his own measurement standard for happiness. If we can find the commonalities that affect happiness and find the policy factors tha ...

Exploratory Data Analysis EDA (Exploratory Data Analysis) analysis with python   show holy respect to python community, for there dedication and wisdom   Dataset related: First, UCL wine dataset: UCI data set is a commonly used standard test data set for machine learning. It is a database for machine learning proposed by the University of ...

Standard zoom 1 Normalization from sklearn.preprocessing import MinMaxScaler def mm(): """ normalization :return: """ mm = MinMaxScaler(feature_range=(2,3)) data = mm.fit_transform([[90,2,10,40],[60,4,15,45],[75,3,13,46]]) print(data) [[3. 2. 2. 2. ] [2. 3. 3. 2.83333333] [2.5 2.5 2.6 3. ]] Zoom to [2,3] Th ...

I Basic knowledge of Request Library methodexplainReturn object.request ()Construction request.get()GET HTML web page, corresponding to HTTP GETThe returned response object contains all the resources of the server.head()Get the page header information, corresponding to HEAD.post()Submit POST request.put()Submit request PUT.patch()Submit lo ...

Official account: Special HouseAuthor: PeterEditor: Peter Hello, I'm Peter~ Continue with questions 11-15 of MySQL classic 50. The specific questions are as follows: Query the information of students who have not completed all coursesQuery the information of students who have at least one course and the same student with student number 01Q ...

catalogue   1, Project background 2, Data source 3, Ask questions 4, Understanding data 5, Data cleaning 1. Import data 2. Select subset 3. Delete duplicate values 4. Missing value processing 5. Standardized treatment 6. Abnormal value handling 6, Analysis content 1. Monthly analysis of consumption 2. User distribution analysis ...