Notes 36
- 💡 Prompt Engineering 101: Deep Dive & Best Practices
- 💡 Prompting: CO-STAR Framework
- 🌊 Time Series Analysis & Forecasting: Deep Dive & Best Practices
- 🌊 HTTP Standards: Quick Guide & Best Practices
- 🌊 React.JS: Deep Dive & Best Practices
- 🌊 NGINX: Deep Dive & Best Practices
- 🌊 SQLite: Deep Dive & Best Practices
- 🌊 DuckDB: Deep Dive & Best Practices with Python
- 🌊 TypeScript: Deep Dive & Best Practices (2025)
- 🌊 Tailwind CSS: Deep Dive & Best Practices
- 🌊 JavaScript: Deep Dive & Best Practices (ES2024)
- 🌊 CSS3: Deep Dive & Best Practices
- 🌊 LightGBM: Deep Dive & Best Practices
- 🌊 HTML5 / CSS3: Deep Dive & Best Practices
- 🌊 CatBoost: Deep Dive & Best Practices
- 🌊 XGBoost: Deep Dive & Best Practices
- 🌊 Statsmodels: Deep Dive & Best Practices
- 📚 Python DS/ML/DL/NLP Libraries — Popular Categories Index
- 🌊 Flask: Deep Dive & Best Practices
- 🌊 Streamlit: Deep Dive & Best Practices
- 🌊 FastAPI: Deep Dive & Best Practices
- 🌊 Scikit-learn: Deep Dive & Best Practices
- 🌊 Docker Technologies: Deep Dive & Best Practices
- 🌊 Pip: Deep Dive & Best Practices
- 🌊 Conda: Deep Dive & Best Practices
- 🌊 Pandas: Deep Dive & Best Practices
- 🌊 NumPy: Deep Dive & Best Practices
- 🌊 MySQL: Deep Dive & Best Practices
- 📘 DSML: Deep Learning Metrics
- ☑️ DSML: MLOps Lifecycle Checklist
- 📘 DSML: Machine Learning Workflow & Lifecycle Illustrated
- 📘 DSML: Machine Learning Metrics
- 📘 DSML: Introduction to Machine Learning
- 📘 Streamlit and Model Serialization in Python
- 📘 TODO — Notes
- 📘 Git & GitHub Basics