Fully Functioned open-source models build in python with the ability to read your own data and make predictions
LLM pipeline
At Upwork, I designed and implemented a project leveraging LLMs to analyze 4,000+ SQL files for optimization. The system evaluated each query based on runtime cost, data scanned, and Snowflake credits consumed—then generated optimized alternatives using PROM. This initiative now saves the company six figures monthly and is used as a foundation for broader cost management and engineering performance monitoring.
A customizable model helps identify a class of an object (in the example files used different fruits) based on dimensions and colors. Could be used for various fraud detection cases.
1st --> download csv file for data
2nd --> use jupyter notebook to run python code
Here you can find a model that allows you to predict the price of a car based on linear and multiple regression models weighing different characteristics of a car according to correlation on a price impact allowing you to use your dataset if needed
1st --> download csv file for data for car price prediction
2nd --> download csv file for data wrangler
3rd -- > use jupyter notebook to run a car price model
4th -- > use jupyter notebook to run a data wrangler
Based on your personal database allows you to determine the price of a house using multiple regression model counting various variables that correlatively affect the price of a house
1st --> download csv file for data
2nd --> use jupyter notebook to run python code
Image Description
By following the link you can find the attribution model for Email Bot Bans using set of aggregated rules where users open emails for a long period of time, but never click the following link.
1st --> download sql file with the script for not_clickers_bots
2nd --> download sql file for too_fast_click_rule script
This script allows you to create a UI display for uploading any files and run through an AI model to analyze the PDF file for specific information
1st Page of a Story reveals avalaibility among the most basic need - Size
2nd Page unveils another import aspect of the house choice - Location
3rd Page allows to complete the search, choosing the optimal plan/price choice using - Floors
4th Page finishes user-journey by letting him choose his final option - House by ID
Here is the example of Accessing Public api and saving it locally on your device
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