Category · 98 articles

AI & Machine Learning

Chunking strategies for RAG: what developers should know

PRACTICAL AI & MACHINE LEARNING · DAY 041

Chunking strategies for RAG: what developers should know

Expona Admin · Oct 27, 2026 · 7 min read

Improving RAG retrieval: AI & ML lessons from production

PRACTICAL AI & MACHINE LEARNING · DAY 042

Improving RAG retrieval: AI & ML lessons from production

Expona Admin · Oct 27, 2026 · 8 min read

Calling LLM APIs from a backend: lessons from production

PRACTICAL AI & MACHINE LEARNING · DAY 043

Calling LLM APIs from a backend: lessons from production

Expona Admin · Oct 27, 2026 · 8 min read

Prompt engineering for developers for AI & ML developers

PRACTICAL AI & MACHINE LEARNING · DAY 044

Prompt engineering for developers for AI & ML developers

Expona Admin · Oct 27, 2026 · 5 min read

Structured output from LLMs: what developers should know

PRACTICAL AI & MACHINE LEARNING · DAY 045

Structured output from LLMs: what developers should know

Expona Admin · Oct 27, 2026 · 8 min read

Function calling and tool use: a practical AI & ML guide

PRACTICAL AI & MACHINE LEARNING · DAY 046

Function calling and tool use: a practical AI & ML guide

Expona Admin · Oct 27, 2026 · 8 min read

Building an AI chat feature: what developers should know

PRACTICAL AI & MACHINE LEARNING · DAY 047

Building an AI chat feature: what developers should know

Expona Admin · Oct 27, 2026 · 9 min read

Evaluating LLM features: AI & ML lessons from production

PRACTICAL AI & MACHINE LEARNING · DAY 048

Evaluating LLM features: AI & ML lessons from production

Expona Admin · Oct 27, 2026 · 8 min read

Reducing LLM costs in Practical AI & Machine Learning

PRACTICAL AI & MACHINE LEARNING · DAY 049

Reducing LLM costs in Practical AI & Machine Learning

Expona Admin · Oct 27, 2026 · 9 min read

AI agents explained in Practical AI & Machine Learning

PRACTICAL AI & MACHINE LEARNING · DAY 050

AI agents explained in Practical AI & Machine Learning

Expona Admin · Oct 27, 2026 · 8 min read

Fine-tuning vs RAG vs prompting: lessons from production

PRACTICAL AI & MACHINE LEARNING · DAY 052

Fine-tuning vs RAG vs prompting: lessons from production

Expona Admin · Oct 27, 2026 · 11 min read

Recommendation systems basics: a practical AI & ML guide

PRACTICAL AI & MACHINE LEARNING · DAY 053

Recommendation systems basics: a practical AI & ML guide

Expona Admin · Oct 27, 2026 · 9 min read

Image classification basics: what developers should know

PRACTICAL AI & MACHINE LEARNING · DAY 054

Image classification basics: what developers should know

Expona Admin · Oct 27, 2026 · 8 min read

OCR and document extraction: what developers should know

PRACTICAL AI & MACHINE LEARNING · DAY 055

OCR and document extraction: what developers should know

Expona Admin · Oct 27, 2026 · 10 min read

Saving and versioning models: a practical AI & ML guide

PRACTICAL AI & MACHINE LEARNING · DAY 056

Saving and versioning models: a practical AI & ML guide

Expona Admin · Oct 27, 2026 · 8 min read

Deploying ML models with FastAPI for AI & ML developers

PRACTICAL AI & MACHINE LEARNING · DAY 057

Deploying ML models with FastAPI for AI & ML developers

Expona Admin · Oct 27, 2026 · 9 min read

Batch vs real-time predictions: best practices explained

PRACTICAL AI & MACHINE LEARNING · DAY 058

Batch vs real-time predictions: best practices explained

Expona Admin · Oct 27, 2026 · 8 min read

Model monitoring in production: best practices explained

PRACTICAL AI & MACHINE LEARNING · DAY 059

Model monitoring in production: best practices explained

Expona Admin · Oct 27, 2026 · 10 min read

MLOps basics: concepts, trade-offs and production lessons

PRACTICAL AI & MACHINE LEARNING · DAY 060

MLOps basics: concepts, trade-offs and production lessons

Expona Admin · Oct 27, 2026 · 10 min read

Experiment tracking with MLflow: lessons from production

PRACTICAL AI & MACHINE LEARNING · DAY 061

Experiment tracking with MLflow: lessons from production

Expona Admin · Oct 27, 2026 · 6 min read