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achieving-optimal-rop-for-oil-and-gas-drilling

This repository contains a Jupyter notebook focused on optimizing the drilling speed, specifically the Rate of Penetration (ROP), in oil and gas exploration wells. The project aims to enhance operational efficiency and reduce costs by leveraging predictive models and PSO optimization techniques.

azuredataengineering

Welcome to the GitHub repository for my Azure Data Engineering project! This repository contains all the code and resources used to transform the Sakila MySQL database into a powerhouse of business intelligence using Azure's cloud computing capabilities.

brooklyndataanalysis

Analysing changes in house sales price from 2015 to 2020 for Brooklyn, using rolling sales data for NY. R is used to run this analysis

data-science-in-oil-and-gas-industry

You will find several interesting Data Science projects in the field of Oil and Gas Industry. From EDA and plotting well profiles to running predictive machine learning models

deep-learning-keras-tf-tutorial

Learn deep learning with tensorflow2.0, keras and python through this comprehensive deep learning tutorial series. Learn deep learning from scratch. Deep learning series for beginners. Tensorflow tutorials, tensorflow 2.0 tutorial. deep learning tutorial python.

educational-tweets-analysis

Identifying if Twitter can be considered as a credible source of educational information. To run the analysis, Spark is used to handle 500GB of 100M tweets on GCP

fictional-lodges-chatbot-llm-

🏨 Fictional Lodges Chatbot using OpenAI Function Calling🤖 An intelligent chatbot for seamless booking experiences at our fictional lodges. Simply chat, provide necessary details, and let the bot handle the booking process through APIs and MySQL integration.

llmbased_sales_icebreaker

Using LLMs the application aims to provide users with relevant, personalized information about individuals to facilitate smoother, more engaging conversations. Ideal for rapid rapport building in networking events, sales pitches, or social gatherings, it offers foundational knowledge about a person's professional background and interests.

llmlingua-prompt-compression-for-cost-effective-rag-with-llms

This project focuses on addressing the limitations and challenges associated with using large generative language models like GPT-3.5 and GPT-4. LLM Lingua, a package designed for efficient language model compression., its approach aims to mitigate token limitations and enhance contextual understanding in language model applications.

llmops-3pipelines-batch_ingestion-finetuning-and-rag_inference

Transform your private LLM into an expert by utilizing a carefully curated dataset leveraging state-of-the-art GPT-4 and then fine-tuning with LLama2 7B.

sarmadafzalj

statanalysis

vector-embeddings-visualization