About me
Quick introduction
I'm currently an AI Engineer Intern at
Groupe SII,
working on a project that involves building a multimodal machine learning system
for recognizing medical document images.
I have a keen interest in artificial intelligence,
full-stack machine learning engineering, human-computer interaction,
and everything in between..
***
"Paddling through the ocean that is Machine Learning." 🧠ðŸ”
experience
Completed
Written
Skills
My technical levelDevelopment
All about the core..Python
90%Java
60%SQL
80%Javascript
70%R
60%Swift
40%Frameworks
Everyone needs supportNumPy
85%pandas
80%matplotlib
70%scikit-learn
70%seaborn
60%OpenCV
70%Flask
70%Streamlit
60%TensorFlow
85%PyTorch
80%NLTK
80%Trax
40%Machine Learning
Theory, theory!Linear and Logistic Regression
85%Decision Trees
70%Exploratory Data Analysis
80%Time Series
70%Convolutional Neural Networks
90%Natural Language Processing
90%Ensemble Models
60%Recommender Systems
60%Multi-modal Learning
70%Cloud and Engineering
Fly Fast & High!AWS Sagemaker
65%Docker
70%Databases and Viz
Storing data and making it prettyMySQL
80%MongoDB
70%Tableau
60%PowerBI
75%Qualification
My personal journeyCertifications
Extra courses I have undertaken
Responsive Web Design
Expiry Date: Does not expire
Python 101 for Data Science
Expiry Date: Does not expire
IBM Data Science Professional Certificate
Expiry Date: Does not expire
Natural Language Processing Specialization
Expiry Date: Does not expire
Projects
Most recent work
PaperWhiz
The project involves developing a conversational recommendation system for machine learning papers. The system is designed to recommend germane papers tailored to a user's specific interests.
GitHub repository Report
Movie Sentiment Analysis
The project involved creating a movie sentiment analysis system based on user reviews, utilizing the Multinomial Naive Bayes algorithm, achieving 86.3% precision on the IMDb dataset, and deploying the NLP model through a Streamlit-powered web application, containerized with Docker.
GitHub repository Report
Fish Detector
The project focused on fine-tuning a YOLOv4 pre-trained model with Darknet framework to count and track two distinct fish species, achieving a 93% Mean Average Precision, while developing TensorFlow-based algorithms for model implementation.
GitHub repository
Portfolio Website
Built a responsive personal portfolio website adaptable to all devices, with ui components and animated interactions to showcase my projects, experience and skills.
GitHub repository
Bird Classifier
The project involved fine-tuning a VGG16 pre-trained model for bird classification, achieving 92% precision on the BIRDS 525 dataset, and developing a user-friendly web application for deployment.
GitHub repository
Classroom Manager
Developed a simple web application that help manage students in a class using Spring Boot. The frontend is built using Angular.
GitHub repositoryBlog
My technical articles
Beyond accuracy: Exploring different metrics for measuring Machine Learning model’s performance
A comprehensive walkthrough to evaluating Machine Learning model’s performance
Read it
How to make your boring macOS terminal look so much better
A 5 minutes guide to customizing your macOS terminal to increase productivity and improve the interface
Read it