𝗙𝗿𝗼𝗺 𝗜 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗼𝗼𝗱 𝗡𝗼𝘁𝗵𝗶𝗻𝗴 𝘁𝗼 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗥𝗔𝗚 𝗔𝗽𝗽
I spent yesterday reading 31 pages of my own NLP notes.
I understood nothing.
I thought the problem was me. It was not. The problem was my method. Reading notes is not learning. I had notes meant for an expert, not for a beginner.
I changed my approach. I stopped reading. Instead, I asked questions. I used simple examples. I refused to use technical terms until I understood the concept.
By the end of the day, I built a RAG app. Here is how I learned the four pillars of NLP.
- Bag of Words Computers only understand math. To process text, you must turn words into numbers.
Imagine you want to sort emails into spam or not spam. You list every word in your emails. You count how many times each word appears. This turns an email into a row of numbers.
The flaw? It ignores word order. "Dog bites man" and "man bites dog" look identical to this method.
- TF-IDF Bag of Words treats every word the same. But "the" is not as important as "viagra."
TF-IDF uses two rules:
- Term Frequency (TF): How often a word appears in one email.
- Inverse Document Frequency (IDF): How rare a word is across all emails.
This math silences filler words like "the" and highlights important, rare words.
- Embeddings Bag of Words thinks "money" and "cash" are unrelated. Embeddings fix this.
Think of a giant map. Every word is a dot on that map. Words with similar meanings sit close together. "Money" and "cash" are neighbors. "Banana" is far away.
The computer learns these locations by looking at the company a word keeps. If "money" and "cash" both appear near "bank" and "pay," the computer places them near each other.
- RAG (Retrieval-Augmented Generation) This is where it all comes together.
If every note in your files is a dot on the map, you can find answers by finding the nearest dots.
The RAG process:
- Turn a question into a dot.
- Find the nearest note-dots on the map.
- Give those notes to an AI.
- Tell the AI to answer using only those notes.
This prevents the AI from guessing or lying. It forces the AI to use your actual data.
I built my app, Synapse, using these steps. I went from zero to a working system in one day.
De les: Stop met lezen. Begin met vragen stellen. Als je een concept niet met een eenvoudige analogie kunt uitleggen, begrijp je het nog niet echt. Bouw iets om te bewijzen dat je het begrijpt.
Bron: https://dev.to/sabimantock/from-i-understood-nothing-to-building-a-rag-app-4033
Optionele leercommunity: https://t.me/GyaanSetuAi