ashishpatel26

Amazing-Feature-Engineering

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

MLOps-Engineering-in-Action

Reference code base for ML Engineering in Action, Manning Publications Author: Ben Wilson

Image-Search-Engine

Image Search Engine with HuggingFace Sentence Transformer

Master-the-LangChain-Prompt-Engineering-Tutorial

LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. Projects for using a private LLM (Llama 2) for chat with PDF files, tweets sentiment analysis.

NER-with-SpanMarker

NER with SpanMarker + Transformers + Spacy

ReadMeCreator-With-LLM

Create informative READMEs effortlessly using AI-driven templates with the README Creator powered by Language Model (LLM). Simplify documentation and enhance project communication.

chainlit

Build Python LLM apps in minutes ⚡️

Chainlit_Tutorials

Chainlit_Tutorials

knowledge_graph

Convert any text to a graph of knowledge. This can be used for Graph Augmented Generation or Knowledge Graph based QnA

LangChain-MasterClass---Build-15-OpenAI-and-LLAMA-2-LLM-Apps-using-Python

LangChain Projects

llm-examples

llm-examples

NeptuneAI_MLOps_Demo

CSV-chatbot

AI chatbot 🤖 for chat with CSV, PDF, TXT files 📄 and YTB videos 🎥 | using Langchain🦜 | OpenAI | Streamlit ⚡

Knowledge-Graph-LLMs

Knowledge Graph LLMs with Neo4j

llm-book

「大規模言語モデル入門」（技術評論社, 2023）のGitHubリポジトリ

superduperdb

🔮 SuperDuperDB: Bring AI to your favourite database! Integrate, train and manage any AI models and APIs directly with your database and your data.

Youtube-Tutorials

Learning Large Language model and NLP Tutorials

llm_chatbot

Web application that allows you to interact with biomedical knowledge graphs and query biomedical questions.

competence-kg

A tutorial on Knowledge Graphs discussing how to model the employee competences within a company

LLM-and-KnowledgeGraph

LLM and KnowledgeGraph

LLM-RLHF-Tuning

LLM Tuning with PEFT (SFT+RM+PPO+DPO with LoRA)

Nebula-Knowledge-Graph-LLM-Langchain

Nebula Knowledge Graph LLM Langchain

RAG-with-KnowledgeGraph

Retrieval Augmented Generation with LangChain, Neo4J Graph DB

streamlit-agent

Reference implementations of several LangChain agents as Streamlit apps

streamlit-example

Example Streamlit app that you can fork to test out share.streamlit.io

blogs

Jupyter notebooks that support my graph data science blog posts at https://bratanic-tomaz.medium.com/

EM_German

Repository for the EM German Model

goingmeta

code and resources used in the Going Meta sessions

langchain2neo4j

Integrating Neo4j database into langchain ecosystem

python_de_learners_data

Repo contains the code, data and supporting documents including presentations, playbooks and additional documents to support learning