Artificial Intelligence
Evaluating LLM Output: Metrics and Testing Frameworks
A practical guide to evaluation pipelines for LLM features: semantic similarity metrics, behavioral testing, regression detection and quality gates.
·4 min read
Tags
Machine Learning
17 articles · Page 1 of 2
Artificial Intelligence
Fine-Tuning Language Models on Domain-Specific Data
Fine-tune language models on your domain with parameter-efficient LoRA and QLoRA: dataset preparation, training strategies and evaluation, on a small budget.
·5 min read
Artificial Intelligence
Retrieval-Augmented Generation: RAG Pipelines That Work
Build effective RAG pipelines in TypeScript: document chunking, embeddings, vector search tuning, prompt construction and retrieval-quality evaluation.
·5 min read
Artificial Intelligence
Vector Database Selection Guide for AI Applications
Compare Pinecone, Weaviate, Qdrant, Milvus and pgvector for AI applications: indexing strategies, query performance, filtering and operational complexity.
·4 min read
Artificial Intelligence
Building Evaluation Frameworks for LLM Applications
Design evaluation pipelines for LLM applications: automated metrics, human evaluation protocols, regression tests, prompt versioning and monitoring.
·5 min read
Artificial Intelligence
Fine-Tuning Language Models for Domain-Specific Tasks
A practical guide to fine-tuning language models on domain data: dataset preparation, training strategies, evaluation and production deployment.
·5 min read
Artificial Intelligence
Responsible AI: Bias Detection and Mitigation
Learn practical techniques for detecting and mitigating bias in machine learning pipelines, from data collection through model deployment and monitoring.
·6 min read
Artificial Intelligence
Federated Learning: Training Models Without Sharing Data
Federated learning concepts, implementation patterns and the practical challenges of training models across distributed devices while preserving privacy.
·6 min read
Artificial Intelligence
Anomaly Detection for Application Monitoring
Anomaly detection for application metrics: statistical methods, z-scores, moving averages, seasonal decomposition and alerting without alert fatigue.
·5 min read
Artificial Intelligence
Vector Databases and Similarity Search
A practical guide to vector databases for similarity search: embeddings, indexing strategies, distance metrics, and choosing between the main options.
·5 min read
Artificial Intelligence
NLP Pipelines for Production Applications
How to build production-ready NLP pipelines: text preprocessing, tokenization, embeddings, classification and entity extraction in TypeScript and Python.
·5 min read
Artificial Intelligence
Building a Recommendation Engine: The Basics
A practical introduction to recommendation systems: collaborative filtering, content-based filtering and hybrid approaches, implemented in TypeScript.
·4 min read