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My name is Nickson M. and I have over 7 years of experience in the tech industry. I specialize in the following technologies: pandas, Python, Scrapy, SQL, Flask, etc.. I hold a degree in Bachelor of Science (BS). Some of the notable projects I’ve worked on include: Cancer detection using Machine Learning, Pick a seat web app, Web app to monitor a small electrical grid, Image Classifier, Android application. I am based in Kampala, Uganda. I've successfully completed 5 projects while developing at Softaims.
My passion is building solutions that are not only technically sound but also deliver an exceptional user experience (UX). I constantly advocate for user-centered design principles, ensuring that the final product is intuitive, accessible, and solves real user problems effectively. I bridge the gap between technical possibilities and the overall product vision.
Working within the Softaims team, I contribute by bringing a perspective that integrates business goals with technical constraints, resulting in solutions that are both practical and innovative. I have a strong track record of rapidly prototyping and iterating based on feedback to drive optimal solution fit.
I’m committed to contributing to a positive and collaborative team environment, sharing knowledge, and helping colleagues grow their skills, all while pushing the boundaries of what's possible in solution development.
Main technologies
Python, Cloud and Machine Learning Platforms
7 years
pandas
2 Years
Python
2 Years
Scrapy
2 Years
Additional skills
Direct hire
Potentially possible
Previous Company
Daba Technologies
Experience Highlights
Cancer detection using Machine Learning
The goal of this project was to build and evaluate a neural network framework for classification of lesions in breast ultrasound images. A classification model based on k-Nearest Neighbour (k-NN) algorithm was built to serve as an evaluation baseline. 4 neural network models were then built using the TensorFlow and Keras deep learning libraries; A fully connected neural network, a custom Convolutional Neural Network (CNN) and two transfer learning networks based on retraining InceptionV3 which is a state of the art general purpose image classification CNN. Neural network approaches outperformed the k-NN. The CNN manages to achieve a low false negative rate and high true positive rate hence a high sensitivity of 0.85. The transfer learning networks underperform due to data limitations.
Pick a seat web app
• Client wanted a web app for reserving seats at an event. Users are presented with the seat layout of the event and can then select a table, pick a seat number then reserve it after verifying their identity using their email address and a ticket number. • Backend can dynamically re-allocate a seat if a user selects a different seat. Completed project successfully. Code has been open sourced with the clients permission
Web app to monitor a small electrical grid
My client wanted a simple web app to monitor a micro electrical grid for a hospital in a remote part of uganda. My contribution; • Developed the front and backend for a web app for remotely monitoring micro electricity grids. • Assisted in the design and coding of a representative grid using an Arduino Mega 2560 board, Transformers, Relays, a SIM800L GSM module, current and voltage sensors. Project open sourced with permission
Image Classifier
A python backend was required for classifying images in a remote location online. My contribution; • Developed an application that classifies images in a user’s cloud storage into specified categories. • Application downloads images from a dropbox folder then classifies and moves them to new directories which are then uploaded back up to dropbox. Utilized: Python, REST API design, Flask, TensorFlow, Keras, Pillow image processing library, ResNet50 Convolutional Neural Network (CNN) architecture, Drop Box API, microservice architecture, unit and integration testing, token authentication, software design patterns Code has been open sourced with permission
Android application
• Led team of 4 developers to build an android mobile phone application for a client who was seeking a Minimum Viable Product to apply for a patent. • Distributed app coding work among team members, led code reviews and built the apps backend. Project completed successfully, patent pending
Education
Makerere University
Bachelor of Science (BS) in Computer engineering
2014-01-01-2018-01-01
Languages
- English
Stackoverflow