Pinned Repositories
AutoGen-Group-Chat
Automatic-number-plate-recognition-with-Python-and-EasyOCR-Computer-vision-tutorial
Automatic number plate recognition with Python and EasyOCR | Computer vision tutorial
awesome-chatgpt-code-interpreter-experiments
Awesome things you can do with ChatGPT + Code Interpreter combo 🔥
awesome-openai-vision-api-experiments
Must-have resource for anyone who wants to experiment with and build on the OpenAI vision API 🔥
Azure-OpenAI-demos
Azure Open AI (demos, documentation, accelerators)
chat_with_structured_data
Computer-Vision-Industry-Use-Cases
Computer Vision Industry Use Cases
Multiple_excel_chat_langchain_using_pandasai
Pandasai multiple excel/csv chat with langchain framework
RFM-Analysis
Recency, frequency, monetary value (RFM) is a model used in marketing analysis that segments a company's consumer base by their purchasing patterns or habits. In particular, it evaluates customers' recency (how long ago they made a purchase), frequency (how often they make purchases), and monetary value (how much money they spend). RFM is then used to identify a company's or an organization's best customers by measuring and analyzing spending habits in order to improve low-scoring customers and maintain high-scoring ones.
Text-Classification-using-LSTM-and-CNN-LSTM
NageshMashette's Repositories
NageshMashette/Multiple_excel_chat_langchain_using_pandasai
Pandasai multiple excel/csv chat with langchain framework
NageshMashette/AutoGen-Group-Chat
NageshMashette/awesome-openai-vision-api-experiments
Must-have resource for anyone who wants to experiment with and build on the OpenAI vision API 🔥
NageshMashette/Azure-OpenAI-demos
Azure Open AI (demos, documentation, accelerators)
NageshMashette/chat_with_structured_data
NageshMashette/Computer-Vision-Matarials
NageshMashette/CustomerResponseChatBot
NageshMashette/Data-Extraction-using-Gen-AI
Data Extraction using generative AI.
NageshMashette/End-to-end-RAG-Implementation-using-Amazon-Bedrock
NageshMashette/GenAI_Indepth
NageshMashette/generative-ai
Sample code and notebooks for Generative AI on Google Cloud
NageshMashette/giskard
🐢 The testing framework for ML models, from tabular to LLMs
NageshMashette/Guardrails-Implementation-in-LLMs
Guardrails implementation in Generative AI powered apps. This app will show you how to put Guardrails in LLMs.
NageshMashette/langchain-tutorials
Overview and tutorial of the LangChain Library
NageshMashette/LangChain_Tutorials
A collection of Python notebooks with tutorials for the LangChain Library.
NageshMashette/LargeLanguageModelsProjects
Large Language Model Projects
NageshMashette/live-video-description
Generate description of live video using OpenCV, GPT4-vision and OpenAI TTS
NageshMashette/Llama-2-Open-Source-LLM-CPU-Inference
Running Llama 2 and other Open-Source LLMs on CPU Inference Locally for Document Q&A
NageshMashette/LLM-Engineering-Crash-Course
LLM Engineering CrashCourse
NageshMashette/LLM-Finetuning
LLM Finetuning with peft
NageshMashette/mcqgen
NageshMashette/NageshMashette
NageshMashette/Phi-2-Small-Language-Model
NageshMashette/Recommendation-systems-with-LLMs
Enhancing recommendation systems with Large Language Models.
NageshMashette/Source-Code-Analysis-using-GenAI
NageshMashette/TextSummerizerEndToEnd
An End to End text summarize project
NageshMashette/The-Grand-Complete-Data-Science-Materials
NageshMashette/Vehicle_Tracking_YOLOV8
NageshMashette/Autogen_with_AzureOpenAI
Auogen_Multi-Agent Chat
NageshMashette/langchain_usecases
🦜🔗 Build context-aware reasoning applications