Data & Research · GitHub ·3 ★

llm-hands-on

A complete guide to NLP and ML for text processing, covering rule-based models, RNNs, CNNs, Transformers, entity detection, sentiment analysis, LLM fine-tuning, RAG, and prompt engineering with tools like Langchain and Ollama.

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Details

Author
Mahiyat
Category
Data & Research
Platform
GitHub
Framework
langchain
Language
jupyter notebook
Stars
3
First indexed
2026-05-15
Last active
2024-12-14
Directory sync
2026-05-15
@Mahiyat

Overview

A complete guide to NLP and ML for text processing, covering rule-based models, RNNs, CNNs, Transformers, entity detection, sentiment analysis, LLM fine-tuning, RAG, and prompt engineering with tools like Langchain and Ollama.

Quick start

git

git clone https://github.com/Mahiyat/llm-hands-on

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What llm-hands-on can do

promptfine-tunsentimentraganaly
  • Prompt — prompt task automation.
  • Fine Tun — fine-tun task automation.
  • Sentiment — sentiment task automation.
  • Rag — Retrieves grounded context before answering.
  • Analy — analy task automation.

Frequently asked questions

What is llm-hands-on?
A complete guide to NLP and ML for text processing, covering rule-based models, RNNs, CNNs, Transformers, entity detection, sentiment analysis, LLM fine-tuning, RAG, and prompt engineering with tools like Langchain and Ollama.
How do I install llm-hands-on?
Use git: `git clone https://github.com/Mahiyat/llm-hands-on`. Full setup details on the source page linked above.
Is llm-hands-on open source?
llm-hands-on is published on GitHub.
What are alternatives to llm-hands-on?
Comparable agents include ragflow, autoresearch, OpenBB. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for llm-hands-on is sourced from GitHub, published by Mahiyat.

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