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LangChain-for-LLM-App-Development
The framework to take LLMs out of the box. Learn to use LangChain to call LLMs into new environments, and use memories, chains, and agents to take on new and complex tasks.Prompt-Engineering-by-OpenAI
In ChatGPT Prompt Engineering for Developers, you will learn how to use a large language model (LLM) to quickly build new and powerful applications.Functions-Tools-and-Agents-with-LangChain
Explore new advancements like ChatGPTโs function calling capability, and build a conversational agent using a new syntax called LangChain Expression Language (LCEL) for tasks like tagging, extraction, tool selection, and routing.Large-Language-Models-with-Semantic-Search
Explore from keyword search to dense retrieval and reranking, which injects the intelligence of LLMs into your search system, making it faster and more effective.Building-Machine-Learning-Demos-with-Gradio
In this course you'll learn to use Gradio to create user-friendly apps with minimal code: Summarize text using a large language model, generate image captions, and chat with an open source LLM. Gain practical knowledge to build interactive demos faster.Quality-and-Safety-for-LLM-Applications
Explore new metrics and best practices to monitor your LLM systems and ensure safety and qualityPython-Chilla-2.0
All the content that I learned through two Courses. One is called "Python Chilla" and the second one is called "100 Days of Machine Learning"Pair-Programming-with-LLM
Learn how LLMs can enhance, debug, and document your code in this new course built in collaboration with GoogleProjects
HuggingFace
HugginFace for BeginnersChatGPT-Python
OpenAI Model integration with Python through OpenAI APIML_pipeline
Machine Learning Project PipelineArslanKAS
Config files for my GitHub profile.Sastaticket-Flight-Competition
SastaTicket Flight ForecastingGetting-Started-with-Mistral
Learn about selecting the right Mistral model for your use case, and get hands-on with features like effective prompting techniques, function calling, JSON mode, and Retrieval Augmented Generation (RAG).Serverless-LLM-Amazon-Bedrock
Youโll learn how to deploy a large language model-based application into production using serverless technologySelenium
This is basic Selenium crash course where I've tried out several automation concepts from testing out websites through actions, captcha, scraping etcQuantization-Fundamentals
Learn to compressing models through methods such as quantization to make them more efficient, faster, and accessibleOil---Gas
Data Analytics on the Insights of Upstream and Downstream of Oil Production for ForecastingSentiment-Analysis
Sentiment Analysis of IMDb reviewsFake-News-Detection
Fake News Detection ModelLangChain-Chat-with-your-Data
Using LangChain learn data loading, splitting, embeddings, and advanced retrieval techniques using over 80 unique loaders. Build question-answering solutions and chatbots with LangChain and LLMs for interactive data interaction.Git---GitHub
Git Cheatsheet for BeginnersFastAPI
Create APIs in Python using FastAPIGCP
MYaseen208
Docker
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