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O
Omotola O.

Omotola O.

Oladotun Omotola | AI Training & Data Annotation

Nigeria flagLagos, Nigeria

Key Skills

Software

No software listed

Top Subject Matter

My strongest subject matter areas are Data Analysis
AI and Machine Learning
Inventory Management

Top Data Types

ImageImage
DocumentDocument
Computer Code ProgrammingComputer Code Programming

Top Task Types

Text SummarizationText Summarization
ClassificationClassification
Emotion RecognitionEmotion Recognition
Computer Programming/CodingComputer Programming/Coding
Data CollectionData Collection
Text GenerationText Generation

Freelancer Overview

I have gained practical experience working with AI-related technologies through my academic and technical projects, particularly the design and implementation of a Fraud Detection System using Explainable AI (XAI) and Federated Learning (FL). During this project, I worked extensively with data preprocessing, data cleaning, feature engineering, handling class imbalance using SMOTE, text vectorization with TF-IDF, and training and evaluating machine learning models using XGBoost. I also utilized SHAP to explain model predictions and improve transparency in AI decision-making. These experiences strengthened my ability to prepare, organize, validate, and analyze datasets for machine learning applications. In addition, I developed experience in reviewing data quality, identifying inconsistencies, categorizing and labeling information for analysis, and ensuring datasets were suitable for AI model training. Through the implementation of Federated Learning, I worked with distributed datasets while maintaining data privacy and model performance, giving me exposure to real-world AI workflows involving data management, annotation preparation, model optimization, and evaluation. This experience has equipped me with strong analytical skills, attention to detail, and a solid foundation in AI training, data labeling, and quality assurance processes.

Labeling Experience

I have experience preparing and organizing data for AI model training through my final-year project on Fraud Detection u

I have experience preparing and organizing data for AI model training through my final-year project on Fraud Detection using Explainable AI (XAI) and Federated Learning (FL). As part of the project, I cleaned and preprocessed datasets, handled missing and inconsistent data, balanced class distributions using SMOTE, and engineered features to improve model performance. I also reviewed and categorized data to ensure quality before training machine learning models with XGBoost. Additionally, I used SHAP to analyze and explain model predictions, helping to validate the accuracy and reliability of the trained models. This experience strengthened my attention to detail, data quality assessment, and understanding of AI training workflows.

Not specified

Education

H

HIIT Plc.

Bachelor of Science (B.Sc.), COMPUTER SCIENCE [LANDMARK UNIVERSITY]. Currently completing professional training in Data Analysis

Bachelor of Science (B.Sc.), COMPUTER SCIENCE [LANDMARK UNIVERSITY]. Currently completing professional training in Data Analysis
Not specified

Work History

C

Company not specified

Front-End Development Intern | Upper Link Limited (March 2024 – September 2024) During my internship at Upper Link Limi

Location not specified
2024 - 2024