Python

Setting up a development environment across multiple operating systems can be tedious. To simplify this, the Multi-Platform Development Tools Installer helps developers install essential tools in a structured and customizable way on Linux, macOS, and Windows. Features Terminal Enhancements zsh oh-my-zsh (with syntax highlighting & autosuggestions) Starship Prompt (Nerd Font preset) fzf (fuzzy finder) zoxide (smart directory jumping, initialized with --cmd cd) Development Environment Tools nvm (Node.js version manager) & Node.js Python (with pip) Docker Git Visual Studio Code PyCharm Community Edition Customizable Installation Choose to install all tools or select specific categories: ...

Introduction to Machine Learning Machine learning is a subset of artificial intelligence that enables systems to learn and improve from experience. Types of Machine Learning Supervised Learning Unsupervised Learning Reinforcement Learning Simple Classification Example Here’s a basic example using scikit-learn: from sklearn.model_selection import train_test_split from sklearn.neighbors import KNeighborsClassifier import numpy as np # Sample data X = np.array([[1, 2], [2, 3], [3, 1], [4, 4]]) y = np.array([0, 0, 1, 1]) # Split data X_train, X_test, y_train, y_test = train_test_split( X, y, test_size=0.25, random_state=42 ) # Train model knn = KNeighborsClassifier(n_neighbors=3) knn.fit(X_train, y_train) # Make predictions predictions = knn.predict(X_test) Key Concepts Feature Selection Model Training Cross-Validation Overfitting vs Underfitting Model Evaluation Stay tuned for more machine learning tutorials! ...