Donly S.

Key Skills

Software

Other

Top Subject Matter

Medical imaging and skin cancer diagnosis (classification)

Network security and intrusion detection (traffic classification)

Medical image data preprocessing pipelines

Top Data Types

Image

Top Task Types

Diagnosis

Classification

Function Calling

Tracking

Freelancer Overview

Machine Learning & Data Science Intern (SIWES) — Skin cancer classification model training (HAM10000, EfficientNetB0/CNN. Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Engineering, Ahmadu Bello University (2021). AI-training focus includes data types such as Medical, DICOM, and Computer Code and labeling workflows including Diagnosis, Classification, and Function Calling.

Labeling Experience

AI Trading Intelligence Platform — ML model integration for trading signals

Other

In your personal AI Trading Intelligence Platform project, you engineered a backend that integrates four machine learning models to generate BTC/USDT trading signals. You implemented model-driven inference logic for trend, momentum, volatility, and sentiment features. You also built a frontend that visualizes signals and tracks positions in real time. • Integrated four ML models for signal generation (trend/momentum/volatility/sentiment) • Implemented backend logic for BTC/USDT signal inference • Built TradingView-inspired charting and overlay UI for signals • Added real-time position tracking in the application

2024 - Present

Machine Learning and Data Science Intern - Industrial Training

Classification

As a Machine Learning and Data Science Intern, you supported hands-on AI and data projects during your industrial training placement. You trained and evaluated models for medical imaging and network security use cases, applying appropriate machine learning techniques. You also built and maintained supporting full-stack and data pipeline components using common web and scripting tools. • Trained an EfficientNetB0-based skin cancer classification model with CNN fallback • Built a network intrusion detection model to classify and flag malicious traffic • Developed a Python/Flask AI-powered trading intelligence platform with ensemble models and chart UI • Produced preprocessing data pipelines and professional lab reports for engineering documentation

2024 - 2025

Machine Learning & Data Science Intern (SIWES) — Financial time-series data pipeline development

OtherTracking

In the Industrial Training role, you developed and deployed preprocessing pipelines for financial time-series data to support AI model training. You prepared time-series inputs for subsequent modeling and experimentation. You also delivered engineering documentation and lab reporting for the created pipelines. • Developed preprocessing pipelines for financial time-series data • Enabled structured training-ready time-series datasets • Supported model development with pipeline outputs • Produced structured reports and documentation

2024 - 2025

Machine Learning & Data Science Intern (SIWES) — Medical image dataset preprocessing for AI training

OtherFunction Calling

In the Industrial Training role, you developed data pipelines to preprocess medical image datasets to make them suitable for model training. Your pipeline work supported preparing inputs consistently across the dataset. You also ensured that preprocessing outputs were documented as part of professional engineering deliverables. • Built preprocessing pipelines for medical image datasets • Standardized dataset preparation for training use • Supported downstream model training and experimentation • Produced documentation and lab reports

2024 - 2025

Machine Learning & Data Science Intern (SIWES) — Intrusion detection model training

OtherClassification

During the same internship, you built and trained a network intrusion detection model to classify and flag malicious network traffic. The work focused on training a supervised model to distinguish malicious from benign traffic patterns. You contributed to implementation artifacts and deployment-ready pipelines. • Trained an intrusion detection classifier for malicious traffic flagging • Focused on classification of network traffic behavior • Developed deployment-oriented workflows for model usage • Supported documentation and reporting as part of engineering practice

2024 - 2025

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Education

Work History