Md. Musa Islam Fahad
@MusaIslamFahadAspiring AI & ML Engineer | Building LLMs, RAG Systems & End-to-End ML Pipelines⚡
Language Breakdown
Lines of code distribution across 26 owned repositories
I-Shaped Developer
I-shapedSpecialist — deep expertise in Jupyter Notebook
Collaboration Network
Global Impact visualization
Repos
26
PRs
0
Growth
+18%
Top Collaborators
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Coding Streak
Contribution activity over the past year
Habiba
@habibanadeemhere
NaveeraRajChuhan
@NaveeraRajChuhan
Umer Farooq
@umerfarooq8743
Hamid raja
@pythonhamid
Sidra Aslam
@Sidraaslam451
Top Repositories
A full end to end data science project analysing 56 years of WTI crude oil prices from exploratory analysis through geopolitical event quantification to ARIMA, Prophet, and LSTM forecasting deployed as an interactive Streamlit dashboard.
Intelligent News Understanding System which classify any news headline or article into 10 categories, detect sentiment, and extract named entities using state of the art NLP.
An intelligent, stateful Customer Support Agent built with LangGraph and LangChain. It categorizes incoming queries, analyses their sentiment, and either routes them to the right specialist handler or escalates negative-sentiment queries to a human agent.
A modern, animated, dark-themed portfolio website built with Next.js 16, TypeScript, Tailwind CSS v4, and Framer Motion.
A fully playable Python + Pygame chess game with human vs. human and human vs. AI modes, powered by Negamax with Alpha-Beta pruning, complete with castling, en passant, pawn promotion, undo and custom board themes.
An Android application for managing student records and academic courses. Built with Java and SQLite, it provides a user-authenticated, offline-first experience for adding, viewing, editing, and deleting students and courses.
A Python + Tkinter desktop travel guide powered by GPT-4o-mini that explores landmarks, restaurants, and local events for any city worldwide, with an interactive map and auto-fetched Wikipedia images.
A supervised ML classification project that predicts sleep disorders- Insomnia, Sleep Apnea, or None from health and lifestyle features including age, BMI, stress level, sleep duration, and blood pressure, using Logistic Regression, Random Forest, and SVM.
A machine learning project on the Kaggle Titanic dataset covering EDA, feature engineering, label encoding, and classification models (Logistic Regression & Random Forest) to predict passenger survival.
Open Source Impact
Contributions to external projects
No external contributions found.