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5000 articles · Page 31 of 50
Model Perspective
Model Perspective
Mar 20, 2023 · Artificial Intelligence

Master Feature Selection with Recursive Elimination (RFE) in Python

Feature Recursive Elimination (RFE) is a powerful feature‑selection technique that iteratively trains a model, discards the weakest features, and repeats until a desired number of features remains, helping prevent overfitting and improve model performance, illustrated with a complete Python example using scikit‑learn.

PythonScikit-learnfeature selection
0 likes · 6 min read
Master Feature Selection with Recursive Elimination (RFE) in Python
Python Programming Learning Circle
Python Programming Learning Circle
Mar 16, 2023 · Fundamentals

13 Amazing Python Features You Might Not Know

This article introduces thirteen lesser‑known Python features—including list stepping, the find method, iterators, doctest, yield statements, dictionary get, for/else and while/else loops, named string formatting, recursion limits, conditional expressions, argument unpacking, the special __hello__ import, and multiline strings—each illustrated with clear code examples.

Advanced FeaturesCode examplesPython
0 likes · 8 min read
13 Amazing Python Features You Might Not Know
Python Programming Learning Circle
Python Programming Learning Circle
Mar 15, 2023 · Game Development

Creating a Code Rain Effect with Python and Pygame

This tutorial demonstrates how to build a classic "code rain" screen using Python's pygame library, guiding readers through imports, window setup, character rendering, and a concise main loop that produces the animated effect in roughly thirty lines of code.

Code RainGame DevelopmentGraphics
0 likes · 6 min read
Creating a Code Rain Effect with Python and Pygame
DataFunTalk
DataFunTalk
Mar 15, 2023 · Artificial Intelligence

Predicting Sunspot Activity with CnosDB and a TensorFlow 1DConv‑LSTM Model

This article demonstrates how to store monthly sunspot numbers in the CnosDB time‑series database and use TensorFlow to build a 1DConv‑LSTM neural network for forecasting sunspot activity, covering data import, database insertion, train‑test splitting, model definition, training, and result visualization.

1DConv LSTMCnosDBPython
0 likes · 11 min read
Predicting Sunspot Activity with CnosDB and a TensorFlow 1DConv‑LSTM Model
Model Perspective
Model Perspective
Mar 14, 2023 · Operations

How Data Envelopment Analysis (DEA) Optimizes Airline Efficiency with Python

Data Envelopment Analysis (DEA) is a non‑parametric technique for evaluating relative efficiency of decision‑making units, with CRS and VRS models explained, followed by a Python implementation using PuLP to assess airline route efficiency and interpret overall, technical, and scale efficiencies.

CRSDEAData Envelopment Analysis
0 likes · 15 min read
How Data Envelopment Analysis (DEA) Optimizes Airline Efficiency with Python
Python Programming Learning Circle
Python Programming Learning Circle
Mar 14, 2023 · Fundamentals

Essential Python Tips and Tricks from A to Z

An extensive collection of Python programming tips and tricks, ranging from built‑in functions like all/any and collections to advanced features such as type hints, virtual environments, and third‑party libraries, presented alphabetically to help developers quickly enhance their code efficiency and readability.

Pythonprogramming
0 likes · 16 min read
Essential Python Tips and Tricks from A to Z
Model Perspective
Model Perspective
Mar 13, 2023 · Fundamentals

Mastering TOPSIS: Step-by-Step Guide with Python Implementation

This article explains the TOPSIS multi‑criteria decision‑making technique, outlines its mathematical formulation, walks through the seven procedural steps, and demonstrates a complete Python example that normalizes data, computes distances, scores alternatives, and ranks the best solution.

PythonTOPSISnormalization
0 likes · 8 min read
Mastering TOPSIS: Step-by-Step Guide with Python Implementation
58UXD
58UXD
Mar 13, 2023 · Fundamentals

Automating 3D Scene Creation in Cinema 4D with Python: From CAD to VR

Learn how to automate the construction of detailed 3D scenes in Cinema 4D using Python, by importing CAD layers, generating walls, doors, windows, furniture, lighting, and cameras, enabling efficient VR visualizations for interior design projects.

3D AutomationCADCinema4D
0 likes · 10 min read
Automating 3D Scene Creation in Cinema 4D with Python: From CAD to VR
Model Perspective
Model Perspective
Mar 11, 2023 · Fundamentals

Mastering the Analytic Hierarchy Process (AHP) with Python: Step‑by‑Step Guide

This article introduces the Analytic Hierarchy Process (AHP), explains its hierarchical modeling, mathematical foundations, step‑by‑step implementation, and provides complete Python code for constructing comparison matrices, calculating weights, and performing consistency checks to ensure reliable results.

Consistency RatioMulti-Criteria Decision MakingPython
0 likes · 9 min read
Mastering the Analytic Hierarchy Process (AHP) with Python: Step‑by‑Step Guide
Python Programming Learning Circle
Python Programming Learning Circle
Mar 11, 2023 · Game Development

Introduction and Basic Usage of the Vizard Virtual‑Reality Development Platform

This article introduces Vizard, a C/C++‑based virtual‑reality development platform with Python support, and demonstrates how to load avatars and objects, create random‑walk behavior, implement dialogue actions, control character movement via keyboard, capture mouse input, and combine these techniques into a complete interactive 3D scene.

3DGame DevelopmentPython
0 likes · 5 min read
Introduction and Basic Usage of the Vizard Virtual‑Reality Development Platform
Model Perspective
Model Perspective
Mar 10, 2023 · Fundamentals

Unlocking the Shoelace Theorem: Fast Polygon Area Calculation Explained

This article explores the “push‑step aggregation” technique featured in the drama “Microscope under the Ming,” revealing that it is essentially the Shoelace Theorem for quickly computing polygon areas, complete with mathematical derivation, visual illustrations, and a Python implementation.

PythonShoelace theoremalgorithm
0 likes · 8 min read
Unlocking the Shoelace Theorem: Fast Polygon Area Calculation Explained
Python Programming Learning Circle
Python Programming Learning Circle
Mar 8, 2023 · Fundamentals

Comprehensive Python Basics: Numbers, Strings, Functions, Data Structures, Classes, and Utilities

This tutorial presents a thorough overview of essential Python concepts, demonstrating numeric operations, string conversions, built‑in functions, diverse data structures, object‑oriented programming techniques, and useful utilities such as file handling, iteration tools, and JSON serialization, all illustrated with clear code examples.

BasicsData StructuresPython
0 likes · 20 min read
Comprehensive Python Basics: Numbers, Strings, Functions, Data Structures, Classes, and Utilities
IT Services Circle
IT Services Circle
Mar 7, 2023 · Frontend Development

Using d3blocks to Create Interactive D3.js Visualizations in Python

The article introduces d3blocks, a Python library that extends D3.js's interactive visualization capabilities to Python, demonstrating how to create interactive scatter, network, Sankey, and image slider charts with just a few lines of code and offering examples with code snippets and GIF illustrations.

D3.jsData VisualizationInteractive Plot
0 likes · 4 min read
Using d3blocks to Create Interactive D3.js Visualizations in Python
Model Perspective
Model Perspective
Mar 6, 2023 · Operations

Master Linear Programming: Theory, Methods, and Python Implementation

Linear programming optimizes a linear objective under linear constraints, and this article explains its theory, common solution methods such as Simplex, Interior‑Point, and Branch‑and‑Bound, illustrates a production‑planning case, and provides a complete Python implementation using SciPy’s linprog function.

Linear ProgrammingPythonbranch-and-bound
0 likes · 7 min read
Master Linear Programming: Theory, Methods, and Python Implementation
Model Perspective
Model Perspective
Mar 3, 2023 · Fundamentals

Unlock Hidden Patterns: A Practical Guide to Factor Analysis with Python

Factor analysis, a statistical technique for uncovering underlying common factors among variables, is explained alongside its distinction from PCA, detailed procedural steps, adequacy tests, and a hands‑on Python implementation using the factor_analyzer library with visualizations and factor rotation methods.

Data preprocessingPythonfactor analysis
0 likes · 10 min read
Unlock Hidden Patterns: A Practical Guide to Factor Analysis with Python
Model Perspective
Model Perspective
Mar 1, 2023 · Artificial Intelligence

Mastering the EM Algorithm: Theory, Math, and Python Implementation

This article explains the Expectation‑Maximization (EM) algorithm, detailing its iterative E‑step and M‑step processes, mathematical formulation, and practical Python implementation for estimating parameters of mixed linear regression models, while highlighting convergence considerations and common pitfalls.

EM algorithmPythonexpectation maximization
0 likes · 12 min read
Mastering the EM Algorithm: Theory, Math, and Python Implementation
Python Programming Learning Circle
Python Programming Learning Circle
Mar 1, 2023 · Fundamentals

30 Handy Python Code Snippets for Everyday Tasks

This article presents 30 concise Python code snippets that can be understood in under 30 seconds, covering common tasks such as checking duplicates, computing byte size, merging dictionaries, measuring execution time, and more, providing quick, practical solutions for everyday programming needs.

Pythoncode snippets
0 likes · 14 min read
30 Handy Python Code Snippets for Everyday Tasks
Python Programming Learning Circle
Python Programming Learning Circle
Mar 1, 2023 · Artificial Intelligence

Introducing Streamlit: A Free Open‑Source Framework for Building Machine‑Learning Apps with Python

Streamlit is a free, open‑source Python framework that lets machine‑learning engineers quickly turn scripts into interactive apps, offering features such as top‑down script execution, widget‑as‑variable handling, caching, GPU support, and seamless integration with version‑control tools, all without requiring separate frontend development.

App DevelopmentCachingData Visualization
0 likes · 9 min read
Introducing Streamlit: A Free Open‑Source Framework for Building Machine‑Learning Apps with Python
Tencent Architect
Tencent Architect
Feb 28, 2023 · Backend Development

Master HTTP/HTTPS Testing with Python httpx and curl: A Practical Guide

This guide explains how to use Python's httpx library and the curl command‑line tool to perform comprehensive HTTP/HTTPS testing—including basic requests, chunked transfers, HTTP/2, SSL/TLS configuration, and dynamic DNS resolution—complete with code examples and setup instructions.

PythoncURLhttp2
0 likes · 13 min read
Master HTTP/HTTPS Testing with Python httpx and curl: A Practical Guide
Python Crawling & Data Mining
Python Crawling & Data Mining
Feb 28, 2023 · Backend Development

How to Fix Common Python Web‑Crawler Issues in PyCharm

This article walks through a Python web‑crawler problem raised in a community, showing step‑by‑step how to start the project, troubleshoot terminal errors in PyCharm, and verify the directory structure using the tree command, providing a clear solution for beginners.

PythonWeb Crawlertroubleshooting
0 likes · 3 min read
How to Fix Common Python Web‑Crawler Issues in PyCharm
Model Perspective
Model Perspective
Feb 27, 2023 · Fundamentals

Mastering Difference-in-Differences: Theory, Example, and Python Implementation

Learn how the Difference-in-Differences (DiD) method estimates policy impacts by comparing treatment and control groups over time, explore its mathematical model, see a concrete traffic‑restriction example, and follow a step‑by‑step Python implementation with data analysis and visualization.

Pythondifference-in-differenceseconometrics
0 likes · 10 min read
Mastering Difference-in-Differences: Theory, Example, and Python Implementation
Model Perspective
Model Perspective
Feb 26, 2023 · Fundamentals

How to Detect Trends with the Mann‑Kendall Test in Python

This article explains how to determine whether a time‑series dataset exhibits a monotonic trend using the non‑parametric Mann‑Kendall test, walks through its statistical foundations, shows the calculation steps with sample sales data, and provides a complete Python implementation for practical analysis.

Mann-KendallPythonstatistics
0 likes · 7 min read
How to Detect Trends with the Mann‑Kendall Test in Python
Python Programming Learning Circle
Python Programming Learning Circle
Feb 25, 2023 · Game Development

Python Mini-Game Collection with Source Code Tutorials

This article presents a series of Python mini-game tutorials, including code for coin-collecting, ping-pong, skiing, space shooter, whack-a-mole, dinosaur runner, match-3, Tetris, snake, 24-point puzzle, alien invasion, tic-tac-toe, and more, offering complete source files and gameplay explanations.

Game DevelopmentPygamePython
0 likes · 36 min read
Python Mini-Game Collection with Source Code Tutorials
DataFunSummit
DataFunSummit
Feb 25, 2023 · Artificial Intelligence

Understanding Reward Model Training in InstructGPT Using Ranking Sequences

This article explains how InstructGPT's reward model is trained by collecting human‑annotated ranking sequences instead of absolute scores, describes the rank‑loss formulation, provides Python code for the model and loss computation, and presents experimental results demonstrating the approach.

InstructGPTPythonRLHF
0 likes · 9 min read
Understanding Reward Model Training in InstructGPT Using Ranking Sequences
Python Programming Learning Circle
Python Programming Learning Circle
Feb 24, 2023 · Fundamentals

Comparing Distributions Between Groups: Visualization and Statistical Methods in Python

This article demonstrates how to compare the distribution of a variable across treatment and control groups using Python, covering data simulation, visual techniques such as boxplots, histograms, KDE, CDF, QQ and ridgeline plots, and statistical tests including t‑test, SMD, Mann‑Whitney, permutation, chi‑square, KS and ANOVA.

A/B testingDistribution ComparisonPython
0 likes · 21 min read
Comparing Distributions Between Groups: Visualization and Statistical Methods in Python
DaTaobao Tech
DaTaobao Tech
Feb 24, 2023 · Artificial Intelligence

Data Preprocessing and Statistical Analysis Techniques in Python

The article reviews essential Python data‑preprocessing and statistical‑analysis tools—including missing‑value imputation, outlier trimming, scaling, binning, knee‑point detection, correlation, chi‑square testing, linear regression, Wilson scoring, PCA weighting, text tokenization and sentiment analysis, plus visualization with matplotlib/seaborn and big‑data access via pyodps.

Machine LearningPythonstatistical analysis
0 likes · 17 min read
Data Preprocessing and Statistical Analysis Techniques in Python
FunTester
FunTester
Feb 23, 2023 · Backend Development

Why RESTful APIs Simplify Testing: A Practical Guide for Test Engineers

This article explains how RESTful API design reduces testing complexity by using unique URIs, standard HTTP methods, and JSON data exchange, and shows how test engineers can extend their frameworks with serialization support and added PUT/DELETE operations.

API testingPythonRESTful
0 likes · 7 min read
Why RESTful APIs Simplify Testing: A Practical Guide for Test Engineers
Python Programming Learning Circle
Python Programming Learning Circle
Feb 21, 2023 · Fundamentals

New Python Standard Library Features: pathlib, secrets, zoneinfo, dataclasses, logging, f‑strings, tomllib, and setuptools

This article introduces the most useful additions and modern replacements in recent Python releases—including pathlib, the secrets module, zoneinfo, dataclasses, proper logging, f‑strings, the built‑in tomllib, and the transition from distutils to setuptools—showing why and how to adopt them in everyday code.

LoggingPythondataclasses
0 likes · 15 min read
New Python Standard Library Features: pathlib, secrets, zoneinfo, dataclasses, logging, f‑strings, tomllib, and setuptools
Python Programming Learning Circle
Python Programming Learning Circle
Feb 18, 2023 · Fundamentals

13 Useful Advanced Python Scripts for Everyday Tasks

This article presents thirteen practical advanced Python scripts covering tasks such as internet speed testing, Google searching, web automation, lyric retrieval, EXIF extraction, OCR, image cartoonization, recycle bin cleaning, Windows version detection, PDF conversion, color conversion, and website status checking, each with ready-to-use code examples.

Code examplesPythonScripting
0 likes · 9 min read
13 Useful Advanced Python Scripts for Everyday Tasks
Python Programming Learning Circle
Python Programming Learning Circle
Feb 17, 2023 · Artificial Intelligence

Building a Simple Probabilistic Programming Language in Python

This article explains the principles of probabilistic programming languages and walks through constructing a basic PPL in Python, covering model definition with latent and observed variables, distribution handling, DAG traversal for log‑density computation, and demonstrates evaluation with example code and visualizations.

Bayesian InferenceDAGPPL
0 likes · 13 min read
Building a Simple Probabilistic Programming Language in Python
21CTO
21CTO
Feb 15, 2023 · Fundamentals

Python’s 2024 Surge: Rust Integration, Web‑UI Frameworks, and Type Safety

Recent Python ecosystem trends highlight the rise of Rust bindings via PyO3, the emergence of pure‑Python web UI frameworks like Streamlit and Pynecone, and growing emphasis on static type safety with tools such as mypy and pydantic, signaling a shift toward higher performance and reliability.

PythonRustpyo3
0 likes · 6 min read
Python’s 2024 Surge: Rust Integration, Web‑UI Frameworks, and Type Safety
Liangxu Linux
Liangxu Linux
Feb 14, 2023 · Fundamentals

2023 Python Practice Exam: 439 Fill‑in, 298 True/False, 32 Short Answer Questions

A comprehensive collection of 2023 Python practice questions—including fill‑in‑the‑blank, true/false, and short‑answer items—covers topics from multimedia and database programming to threading, networking, GUI, exception handling, file I/O, OOP, and core language features, with sample code snippets for deeper understanding.

Pythonexamfill-in-the-blank
0 likes · 8 min read
2023 Python Practice Exam: 439 Fill‑in, 298 True/False, 32 Short Answer Questions
Python Programming Learning Circle
Python Programming Learning Circle
Feb 13, 2023 · Artificial Intelligence

Python License Plate Detection and Recognition Using OpenCV and Tesseract

This tutorial walks through building a Python program that detects and reads vehicle license plates by preprocessing images with OpenCV, extracting contours, isolating the plate region, and applying Tesseract OCR to convert the characters into text, complete with environment setup and code examples.

PythonTesseract OCRlicense-plate-recognition
0 likes · 7 min read
Python License Plate Detection and Recognition Using OpenCV and Tesseract
Python Programming Learning Circle
Python Programming Learning Circle
Feb 11, 2023 · Fundamentals

Common Mistakes When Using Python Lambda Functions and How to Avoid Them

This article explains what Python lambda (anonymous) functions are, shows their syntax, demonstrates typical use cases with built‑in functions and pandas, and outlines four common pitfalls—returning values, assigning to variables, ignoring better alternatives, and overusing them—while providing code examples and best‑practice recommendations.

LambdaPythonanonymous function
0 likes · 7 min read
Common Mistakes When Using Python Lambda Functions and How to Avoid Them
Top Architect
Top Architect
Feb 11, 2023 · Backend Development

XNote – Lightweight Personal Note System: Features, Architecture, and Installation Guide

This article introduces XNote, a lightweight personal note system with rich data management, cross‑platform support, and extensible plugins, detailing its key features, system architecture, directory layout, required dependencies, and step‑by‑step installation and configuration instructions for Python environments.

Open SourcePythonWeb Development
0 likes · 11 min read
XNote – Lightweight Personal Note System: Features, Architecture, and Installation Guide
Python Programming Learning Circle
Python Programming Learning Circle
Feb 9, 2023 · Fundamentals

Understanding Loop Structures in Python: for, while, break, continue, and Nested Loops

This article explains why loops are needed in programming, introduces Python's for‑in and while loops, demonstrates their syntax with practical examples—including range variations, break/continue statements, and nested loops such as the multiplication table—and provides exercises on prime checking and GCD/LCM calculation.

LoopsPythonfor
0 likes · 9 min read
Understanding Loop Structures in Python: for, while, break, continue, and Nested Loops
Model Perspective
Model Perspective
Feb 8, 2023 · Artificial Intelligence

Mastering Feature Selection: From Filters to Embedded Methods in Python

This article explains why feature selection is crucial for machine learning, outlines the general workflow, compares filter, wrapper, embedded, and synthesis approaches, and provides practical Python examples—including Pearson correlation, chi‑square tests, mutual information, variance selection, recursive elimination, L1 regularization, and PCA—complete with code snippets and visualizations.

Pythonfeature selectionstatistics
0 likes · 20 min read
Mastering Feature Selection: From Filters to Embedded Methods in Python
Python Programming Learning Circle
Python Programming Learning Circle
Feb 8, 2023 · Fundamentals

Measuring Execution Time and Memory Usage in Python

This article introduces four practical methods for monitoring Python code performance—using the built‑in time module, the %%time IPython magic, line_profiler for per‑line timing, and memory_profiler for detailed memory usage—complete with code examples and interpretation of results.

MemoryPythonline_profiler
0 likes · 7 min read
Measuring Execution Time and Memory Usage in Python
Python Programming Learning Circle
Python Programming Learning Circle
Feb 4, 2023 · Artificial Intelligence

Hand Gesture Recognition Using OpenCV: Video Capture, Skin Detection, and Contour Processing in Python

This article demonstrates a Python-based hand‑gesture recognition pipeline using OpenCV, covering video capture, skin detection via YCrCb conversion, contour extraction, and visualization, with complete source code and step‑by‑step explanations suitable for beginners.

Contour ExtractionHand GesturePython
0 likes · 6 min read
Hand Gesture Recognition Using OpenCV: Video Capture, Skin Detection, and Contour Processing in Python
IT Services Circle
IT Services Circle
Feb 4, 2023 · Fundamentals

Using plottable to Create Highly Customizable Tables in Python

This article introduces the Python library plottable, which builds highly customizable tables on top of Matplotlib, and provides a complete example showing data loading, column styling, and rendering of a styled table along with additional recommended reading links.

Data VisualizationMatplotlibPython
0 likes · 6 min read
Using plottable to Create Highly Customizable Tables in Python
Liangxu Linux
Liangxu Linux
Feb 1, 2023 · Fundamentals

20 Must‑Try Python3 Open‑Source Projects to Boost Your Coding Skills

This guide explains why actively experimenting with code beats passive reading, outlines a step‑by‑step method for mastering source code, and presents a curated list of twenty free Python3 projects—complete with executables and source—that are ideal for beginners and advanced learners alike.

AIOpen SourceProjects
0 likes · 7 min read
20 Must‑Try Python3 Open‑Source Projects to Boost Your Coding Skills
Sohu Tech Products
Sohu Tech Products
Feb 1, 2023 · Artificial Intelligence

ChatGPT Writes AI: Building an MNIST Classifier with Keras Using ChatGPT

This article demonstrates how a machine‑learning enthusiast used ChatGPT to generate, modify, and refine Keras code for training, evaluating, visualizing, and deploying a neural‑network model that classifies handwritten digits from the classic MNIST dataset, showcasing the full development workflow.

ChatGPTKerasMNIST
0 likes · 4 min read
ChatGPT Writes AI: Building an MNIST Classifier with Keras Using ChatGPT
21CTO
21CTO
Feb 1, 2023 · Fundamentals

Inside CPython’s Garbage Collector: Ref Counting, Cycle Detection & Generational Tricks

CPython’s garbage collector combines reference counting with a cyclic collector that uses generational strategies, fat pointers, and optimized object structures to efficiently identify and reclaim unreachable objects, handling cycles, weak references, and memory layout details while minimizing overhead.

Garbage CollectionGenerational GCPython
0 likes · 21 min read
Inside CPython’s Garbage Collector: Ref Counting, Cycle Detection & Generational Tricks
21CTO
21CTO
Jan 27, 2023 · Fundamentals

Which Programming Languages Dominated the 2022 Job Market? Top 8 Revealed

Based on analysis of over 12 million developer job postings from October 2021 to November 2022, DevJobsScanner identified the eight programming languages with the highest demand in 2022, highlighting JavaScript/TypeScript’s dominance, the rise of Python and Java, and emerging trends for Go, C#, PHP, C/C++, and Ruby.

2022 demandJavaScriptJob market
0 likes · 7 min read
Which Programming Languages Dominated the 2022 Job Market? Top 8 Revealed
Model Perspective
Model Perspective
Jan 17, 2023 · Fundamentals

Master Six Classic Sorting Algorithms in Python: From Bubble to Quick Sort

This article introduces six fundamental sorting algorithms—bubble, selection, insertion, shell, merge, and quick sort—explains their principles, provides Python implementations with code examples, visual animations, and compares built‑in sorting methods, helping readers understand and apply these techniques effectively.

PythonQuick SortSorting Algorithms
0 likes · 16 min read
Master Six Classic Sorting Algorithms in Python: From Bubble to Quick Sort
Model Perspective
Model Perspective
Jan 14, 2023 · Fundamentals

Python Data Structures: Strings, Lists, Tuples, Dicts, Sets, Stacks & Queues

This article introduces essential Python data structures—including strings, lists, tuples, dictionaries, sets, as well as stack and queue implementations—explaining their characteristics, usage, and providing clear code examples to illustrate creation, indexing, slicing, and common operations.

Data StructuresListsPython
0 likes · 9 min read
Python Data Structures: Strings, Lists, Tuples, Dicts, Sets, Stacks & Queues
Model Perspective
Model Perspective
Jan 13, 2023 · Artificial Intelligence

Master Classic Modeling with Python: LP, Graphs, Clustering, PCA & More

This article presents Python implementations of classic mathematical modeling techniques—including linear programming with PuLP, shortest‑path analysis using NetworkX, K‑means and hierarchical clustering, principal component analysis, frequent‑pattern mining with FP‑Growth, and linear regression and K‑nearest‑neighbors—providing code snippets, explanations, and visualizations to guide readers through each method.

Frequent Pattern MiningPCAPython
0 likes · 12 min read
Master Classic Modeling with Python: LP, Graphs, Clustering, PCA & More
Model Perspective
Model Perspective
Jan 11, 2023 · Fundamentals

Master Sensitivity Analysis: Theory, Methods, and Python SALib Walkthrough

This article introduces sensitivity analysis, explains its key concepts, indices, and selection criteria, then details various methods—including OAT, derivative‑based, regression, variance‑based, FAST, Morris, and Sobol—followed by practical Python examples using the SALib library with code and visualizations.

FASTMorrisPython
0 likes · 18 min read
Master Sensitivity Analysis: Theory, Methods, and Python SALib Walkthrough
Model Perspective
Model Perspective
Jan 10, 2023 · Fundamentals

Fit Real-World Data with Fourier Series Using Python

This article explains Fourier series theory, demonstrates how to remove linear trends from monthly CO₂ data, and shows step‑by‑step Python code using SciPy's curve_fit to fit and predict the data with a 100‑term Fourier expansion.

PythonTime Series Analysisdata fitting
0 likes · 6 min read
Fit Real-World Data with Fourier Series Using Python
Efficient Ops
Efficient Ops
Jan 9, 2023 · Operations

Boost Ops Efficiency: 5 Python Scripts Every Sysadmin Should Use

This article explains how Python can automate common operations tasks—remote command execution, log parsing, system monitoring with alerts, bulk software deployment, and backup/restore—providing code examples for each and highlighting additional tools that help sysadmins improve efficiency and reduce errors.

MonitoringPythonSysadmin Scripts
0 likes · 9 min read
Boost Ops Efficiency: 5 Python Scripts Every Sysadmin Should Use
IT Services Circle
IT Services Circle
Jan 9, 2023 · Operations

Python Server Resource Monitoring and Alerting Scripts

This article presents Python scripts for server‑side and client‑side resource monitoring, automatically checking CPU, memory, disk usage and network traffic, storing alerts in MySQL and optionally sending notifications via email or Enterprise WeChat, with deployment instructions and cron scheduling.

AlertingPythonServer monitoring
0 likes · 19 min read
Python Server Resource Monitoring and Alerting Scripts
Model Perspective
Model Perspective
Jan 5, 2023 · Fundamentals

Modeling Age‑Structured Populations with the Leslie Matrix in Python

This article explains the Leslie matrix model for age‑structured population forecasting, outlines its mathematical formulation, demonstrates how to build and solve it using Python code, and shows how to derive demographic indicators such as average age, lifespan, aging index, and dependency ratio.

Leslie matrixPythonage‑structured model
0 likes · 9 min read
Modeling Age‑Structured Populations with the Leslie Matrix in Python
Meituan Technology Team
Meituan Technology Team
Jan 5, 2023 · Backend Development

Automated SDK Generation for Meituan Open Platform

The article details Meituan Open Platform’s approach to automatically generate multi‑language SDKs with rich parameter models, covering overall design, code‑generation via DSL templates, CI/CD integration, and the resulting efficiency gains for third‑party developers integrating over a thousand OpenAPI endpoints.

API automationCI/CDJava
0 likes · 23 min read
Automated SDK Generation for Meituan Open Platform
Model Perspective
Model Perspective
Jan 4, 2023 · Fundamentals

Mastering Fuzzy Mathematics: Membership Functions and Python Implementations

This article introduces fuzzy mathematics, explains how fuzzy sets and membership functions quantify vague concepts, and provides Python code using the scikit‑fuzzy library to implement various membership functions such as triangular, Gaussian, S‑shaped, and polynomial types, complete with plotting examples.

Pythonfuzzy logicfuzzy mathematics
0 likes · 11 min read
Mastering Fuzzy Mathematics: Membership Functions and Python Implementations
Python Programming Learning Circle
Python Programming Learning Circle
Dec 31, 2022 · Artificial Intelligence

A Beginner’s Guide to Data Preprocessing for Machine Learning in Python

This tutorial walks beginners through the essential steps of data preprocessing for any machine learning model, covering library imports, dataset loading, handling missing values, encoding categorical features, splitting into train‑test sets, and applying feature scaling using Python’s scikit‑learn.

Data preprocessingOne-hot encodingPython
0 likes · 11 min read
A Beginner’s Guide to Data Preprocessing for Machine Learning in Python
Model Perspective
Model Perspective
Dec 30, 2022 · Fundamentals

How PCA Transforms Supplier Evaluation with Weighted Scores

This article explains the Principal Component Analysis (PCA) method, outlines its step‑by‑step weighting algorithm, and demonstrates a complete Python implementation that converts supplier metrics into objective scores using scikit‑learn.

PCAPythonScikit-learn
0 likes · 9 min read
How PCA Transforms Supplier Evaluation with Weighted Scores
Python Programming Learning Circle
Python Programming Learning Circle
Dec 28, 2022 · Fundamentals

13 Advanced Python Scripts for Everyday Tasks

This article presents thirteen advanced Python scripts covering tasks such as internet speed testing, Google searching, web automation, lyric retrieval, EXIF extraction, OCR, image cartoonization, recycle bin cleaning, image enhancement, Windows version detection, PDF-to-image conversion, hex-to-RGB conversion, and website status checking, each with code examples.

Advanced ScriptsImage processingPython
0 likes · 10 min read
13 Advanced Python Scripts for Everyday Tasks
Efficient Ops
Efficient Ops
Dec 28, 2022 · Operations

Mastering Ansible: 16 Visual Guides to Automate Your Operations

Ansible, a rapidly popular open‑source automation tool built on Python, enables batch system configuration, program deployment, and command execution through thousands of built‑in modules, offering a simple yet powerful solution for operations engineers, illustrated here with 16 comprehensive images.

AnsiblePythonautomation
0 likes · 3 min read
Mastering Ansible: 16 Visual Guides to Automate Your Operations
Python Programming Learning Circle
Python Programming Learning Circle
Dec 27, 2022 · Backend Development

Generating QR Codes with Python's segno Library

This tutorial explains how to install the segno Python package and use it to create simple and customized QR codes for URLs, Wi‑Fi credentials, vCards, artistic designs, and in‑memory images, providing complete code examples and practical ideas for personal and social applications.

PythonQR codeWiFi
0 likes · 8 min read
Generating QR Codes with Python's segno Library