đHands-on Tutorial: Fine-tune a Cross-Encoder for Semantic Similarity
đĽ Why Fine-Tune a Cross-Encoder? 1. More Accurate Semantic Judgments: 2. Adapting to Domain-Specific Data Without fine-tuning, the model might miss these domain...
Category: Natural Language Processing – NLP
đBuilding a Full-Stack Hybrid Search System (BM25 + Vectors + Cross-Encoders) with Docker
1ď¸âŁ Introduction Search is at the heart of every AI application. Whether youâre building a legal research assistant, a compliance monitoring tool, or an LLM-pow...
đBM25-Based Searching: A Developerâs Comprehensive Guide
đ Introduction: Why BM25 Matters Imagine you type âbest Python tutorialsâ into a search engine. Millions of web pages match your queryâbut how does the engine k...
AI & ML/Computer Vision/Deep Learning/Deep Reinforcement Learning/Explainable AI/GenAI/LLMs/Medical Imaging/Natural Language Processing - NLP/Software Development
Provenance in AI: Tracking AI Lineage with Signed Provenance Logs in Python – Part 2
In modern AI pipelines, provenance â the lineage of datasets, models, and inferences â is becoming as important as accuracy metrics. Regulators, auditors, and e...
AI & ML/Computer Vision/Deep Learning/Deep Reinforcement Learning/Explainable AI/GenAI/LLMs/Medical Imaging/Natural Language Processing - NLP/Software Development
Provenance in AI: Why It Matters for AI Engineers – Part 1
1. Introduction: Why AI Needs a Paper Trail Imagine debugging a complex AI pipeline without knowing which version of the dataset was used, how the features were...
Question Answer Chatbot using RAG, Llama and Qdrant
1. Introduction I have created this teaching chatbot that can answer questions from class IX, subject SST, on the topic “Democratic politics“. I hav...
On Emergent Abilities of Large Language Models
An ability is emergent if it is not present in smaller models but is present in larger models. [1] Scaling up language models has been shown to improve predicta...
Prompt Engineering Deep Dive: Parameters, Chains, Reasoning, and Guardrails
1. Introduction Prompt engineering is the practice of designing and refining the text (prompt) that we pass to a Generative AI (GenAI) model. The prompt acts as...
Text Clustering and Topic Modeling using Large Language Models (LLMs)
1. Introduction Text clustering is an unsupervised approach that helps in discovering patterns in data. Grouping similar texts according to their semantic conte...
Text Classification using Large Language Models (LLMs)
1. Introduction A common task in natural language processing (NLP) is text classification. Use cases of text classification include sentiment analysis, intent d...