10ac_city_traffic_data_warehouse_week2

10ac_news_correlation_week0

10ac_tellco_week1

10ac_youtube_week3

automated-storyboard-synthesis-for-digital-advertising

causal-inference

Optimizing driver placement for Gokada, Nigeria’s largest last-mile delivery service, to increase order fulfillment and improve client satisfaction. Analyzes delivery data to identify issues and recommend optimal driver locations.

contract-advisor-rag

The objective is to build, evaluate, and improve a Retrieval-Augmented Generation (RAG) system for Contract Q&A, simulating interaction with a contract by asking questions and getting precise answers.

disaster-tweets-classification

fabric-defect-detection

The aim of this project is to develop a model capable of detecting fabric defection.

fifa-world-cup-2022-tweets

The dataset includes tweets in English containing the hashtag #WorldCup2022.

house-sales-in-king-county-usa

This dataset contains house sale prices for King County, which includes Seattle. It includes homes sold between May 2014 and May 2015.

ivy

The Unified Machine Learning Framework

llm-fine-tunning_amharic

Fine-tuning language models for Amharic news classification into categories such as Local News, Entertainment, Sports, Business, International News, and Politics.

llm_fine_tunning_api

A project for scraping and preprocessing data to enhance large language models (LLMs). Provides a scalable and flexible foundation for developing APIs focused on fine-tuning LLMs.

precision-rag

Precision RAG is a project focused on building enterprise-grade Retrieval-Augmented Generation (RAG) systems with a strong emphasis on prompt tuning. This repository provides tools and scripts to facilitate data generation, prompt tuning, evaluation, and deployment of RAG systems.

redash-chatbot

scalable-backtesting-infrastructure

This project aims to design and build a reliable, large-scale trading data pipeline for a startup called Mela, which wants to make it simple for everyone to enter the world of cryptocurrencies. The pipeline will enable investors to run backtests that simulate current and past particular situations as well as their trend over time.

spot-the-mask

Leveraging the power of EfficientNetB0, I built a binary classification system capable of identifying individuals wearing masks in images. This project, developed in Python and Keras, contributes to public health and safety initiatives by providing a readily deployable solution for mask detection in real-world settings.

yohanes213

Config files for my GitHub profile.