Zipf’s Law in Natural Language Processing
By Alby Abraham SamContinue reading on Medium »
Artificial Intelligence, data-science, naturallanguageprocessing
naturallanguageprocessing
Artificial Intelligence, data-science, Machine Learning, naturallanguageprocessing, python
Understanding NLP Token Classification Tasks: NER, POS Tagging, and Chunking
1. Introduction to NLP & Token ClassificationContinue reading on Medium »
Artificial Intelligence, deep-learning, large-language-models, Machine Learning, naturallanguageprocessing
How Encoder Transformers Actually Understand Language
The evolution of the attention mechanism in encoder only models. From BERT to ModernBERTThe AI world is currently obsessed with models that talk. GPT-4, Claude 3, and Llama have become the charismatic orators of our era, generating essays, code, and po…
Artificial Intelligence, Automation, data-science, naturallanguageprocessing, nlp
How NLP is Quietly Controlling the Internet (And You Don’t Even Notice)
You wake up.
Check your phone.
Scroll through social media.
Search something on Google.Continue reading on Medium »
ai-limitation, Artificial Intelligence, Machine Learning, naturallanguageprocessing, nlp
Why AI Struggles with Context and Ambiguity
The same sentence can mean different things, and that is where AI models often fail.Continue reading on Medium »
Artificial Intelligence, computers, enabling, naturallanguageprocessing, understanding
What is natural language processing (NLP)?
Natural Language Processing (NLP) is a field within Artificial Intelligence that focuses on enabling computers to understand, interpret…Continue reading on Medium »
Artificial Intelligence, data-science, Machine Learning, naturallanguageprocessing, nlp
Why NLP Models Still Fail in Real-World Applications
AI models perform well on clean data, but real-world language is far more complex.Continue reading on Medium »
ai, generative-ai-tools, llm, naturallanguageprocessing, sql
Teaching Your SQL Generator to Fix Its Own Mistakes
Part 4 of the SQL Query Generator Series — The Self-Correction Retry LoopThis series builds a complete natural language → SQL system step by step. Part 1 built the schema-aware generator. Part 2 added safety validation. Part 3 wired in execution and re…
Artificial Intelligence, embedding, Machine Learning, naturallanguageprocessing
Embeddings Explained: How AI Turns Words Into Numbers That Actually Mean Something
The surprisingly elegant math that lets computers understand that “dog” and “puppy” are related — and why this powers everything from…Continue reading on Medium »
ai, generative-ai-use-cases, llm, naturallanguageprocessing, sql-server
Closing the Loop: Executing LLM-Generated SQL and Presenting Results
Part 3 of the SQL Query Generator Series — From Validated Query to Real Data*Previously in this series: In Part 1, we built a schema-aware LLM pipeline that turns a plain English question into a T-SQL query. In Part 2, we added a `SQLValidator` that pa…