Set up your development environment on Linux, macOS, and Windows using a few simple scripts. Repository Overview In the fernand3z/dev-toolbox repository, you’ll find a set of scripts designed to automatically install your favorite development tools—such as zsh, oh‑my‑zsh, starship, nvm/node, python3/pip3, docker, git, VS Code, and PyCharm Community Edition—on Linux, macOS, and Windows. The repository is organized into a few key directories and files: fernand3z/dev-toolbox/ ├── install.sh # The master installer that sets permissions and lets you choose an OS. ├── linux/ │ └── install_linux.sh # A universal Linux installer that auto-detects your package manager. ├── macos/ │ └── install_macos.sh # A macOS installer using Homebrew. └── windows/ ├── install_windows.sh # A Windows installer using winget. └── run_install_windows.bat # A batch file that requests admin privileges. Each platform has its own script, but the master installer (install.sh) ties everything together. ...

Why Rust? Rust has been Stack Overflow’s most loved programming language for several years running. Let’s explore what makes it special. Memory Safety Without Garbage Collection One of Rust’s most notable features is its guarantee of memory safety without using a garbage collector. This is achieved through its ownership system: fn main() { let s1 = String::from("hello"); let s2 = s1; // s1 is moved to s2 // println!("{}", s1); // This would cause a compile error println!("{}", s2); // This works fine } Zero-Cost Abstractions Rust provides high-level features without runtime overhead: ...

What are Docker Containers? Docker containers are lightweight, standalone packages that include everything needed to run a piece of software. Basic Docker Commands Here are some essential Docker commands you’ll use daily: # Pull an image docker pull nginx # Run a container docker run -d -p 80:80 nginx # List running containers docker ps # Stop a container docker stop container_id Creating a Dockerfile Here’s a simple Dockerfile for a Node.js application: ...

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! ...

Understanding Kubernetes Kubernetes (K8s) is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. Key Concepts Pods Services Deployments ConfigMaps Secrets Basic Pod Definition apiVersion: v1 kind: Pod metadata: name: nginx-pod labels: app: nginx spec: containers: - name: nginx image: nginx:1.14.2 ports: - containerPort: 80 Simple Deployment apiVersion: apps/v1 kind: Deployment metadata: name: nginx-deployment spec: replicas: 3 selector: matchLabels: app: nginx template: metadata: labels: app: nginx spec: containers: - name: nginx image: nginx:1.14.2 Common Commands # Get cluster info kubectl cluster-info # Create resources kubectl apply -f deployment.yaml # List resources kubectl get pods kubectl get deployments Stay tuned for more Kubernetes tutorials! ...