🌊 NumPy: Deep Dive & Best Practices
Concise, clear, and validated revision notes on NumPy — structured for beginners and practitioners.
Kalyan Narayana
🌊 MySQL: Deep Dive & Best Practices
Concise, clear, and validated revision notes on MySQL — structured for beginners and practitioners.
🧭 DSML: Machine Learning Lifecycle - Comprehensive Guide
Concise, clear, and validated Comprehesive guide revision notes on Machine Learning Lifecycle, MLOps, Metrics, Code Snippets — structured for beginners and practitioners.
📘 DSML: Deep Learning Metrics
Concise, clear, and validated revision notes on Machine Learning, Deep Learning, and Data Science Metrics — structured for beginners and practitioners.
☑️ DSML: MLOps Lifecycle Checklist
A validated and novice-friendly master checklist for the DSML lifecycle — Plan, Data, Model, and Deploy — aligned with Google, AWS, and Microsoft MLOps frameworks.
📘 DSML: Machine Learning Workflow & Lifecycle Illustrated
Concise, clear, and validated revision notes on the end-to-end Machine Learning Lifecycle — phases, checklists, pitfalls, and trusted references.
📘 DSML: Machine Learning Metrics
Concise, clear, and validated revision notes on Machine Learning, Deep Learning, and Data Science Metrics — structured for beginners and practitioners.
📘 DSML: Introduction to Machine Learning
A clear, concise, and validated introduction to Machine Learning — structured for beginners with definitions, examples, and authoritative references.
📗 ArXiv: Essential Guides for DS / ML / DL
A unified, validated roadmap combining essential, comprehensive, and deep-dive arXiv papers for Data Science, Machine Learning, and Deep Learning — curated in apt learning order for clarity and confidence.
📗 ArXiv: Essential Reading for LLMs
A curated list of the most influential AI & LLM papers — clearly categorized and explained for beginners.