K M Rakeen Abtahee

Professional, hardworking, and results-driven software engineer with over a year of real-world experience. Proficient in various programming languages and technologies, with a strong focus on creating efficient and scalable code. Adept at collaborating with cross-functional teams to deliver high-quality products on time and within budget. Seeking to leverage expertise to contribute to a dynamic company's success.

• Enjoy playing PC games, listening to music, and watching movies.
• Passionate about discovering new places, taking nature walks, and exploring food, sharing these experiences with friends and family.

MQ Uni app | Flutter (Dart) | 04/2024

• Developed a demo application utilizing Flutter (Dart) and Firebase, designed to assist students in navigating the campus, ordering coffee, and booking and paying for parking. Firebase was integrated to provide a real-time database and user authentication features. I also implemented a responsive UI/UX design to ensure cross-platform compatibility, and used Figma to design for the iPhone 15. Additionally, I utilized Flutter's state management techniques to handle data efficiently.

MNIST Deep Learning Classifier (AI Text) | Python | 03/2024,

• Developed and optimized a deep learning classifier with Keras and KerasTuner for the MNIST dataset, achieving a high test accuracy of around 98.2%. I employed rigorous evaluation methods to validate the model's performance and ensure its robustness.

Image Classifier for different weather using the Multi-class Weather Dataset (AI Vision) | Python | 05/2024,

• Developed and implemented an image classifier with TensorFlow and Keras, attaining overall accuracies of 78.7% for the Simple classifier, 82.2% for the Complex classifier, and 79.3% for the CNN classifier. The Multi-class Weather Dataset was used to train and test the models for weather classification purposes.

• Enjoy playing PC games, listening to music, and watching movies.
• Passionate about discovering new places, taking nature walks, and exploring food, sharing these experiences with friends and family.

Created a regression testing framework for the company product pipeline that has tracked down vulnerabilities and errors that would have otherwise gone unnoticed and increased production efficiency by 40%.

MQ Uni app | Flutter (Dart) | 04/2024

• Developed a demo application utilizing Flutter (Dart) and Firebase, designed to assist students in navigating the campus, ordering coffee, and booking and paying for parking. Firebase was integrated to provide a real-time database and user authentication features. I also implemented a responsive UI/UX design to ensure cross-platform compatibility, and used Figma to design for the iPhone 15. Additionally, I utilized Flutter's state management techniques to handle data efficiently.

MNIST Deep Learning Classifier (AI Text) | Python | 03/2024,

• Developed and optimized a deep learning classifier with Keras and KerasTuner for the MNIST dataset, achieving a high test accuracy of around 98.2%. I employed rigorous evaluation methods to validate the model's performance and ensure its robustness.

Image Classifier for different weather using the Multi-class Weather Dataset (AI Vision) | Python | 05/2024,

• Developed and implemented an image classifier with TensorFlow and Keras, attaining overall accuracies of 78.7% for the Simple classifier, 82.2% for the Complex classifier, and 79.3% for the CNN classifier. The Multi-class Weather Dataset was used to train and test the models for weather classification purposes.