emkaymoin 0.5.0

Khaja Moinuddin Mohammed's data science portfolio as a Python package

emkaymoin

Khaja Moinuddin Mohammed's data science portfolio — as a Python package.

pip install emkaymoin

import emkaymoin as emkay

emkay.whoami()        # who is emkay?
emkay.summary()       # full snapshot in one command
emkay.roast()         # go on, you deserve it
emkay.puzzle()        # solve a data riddle to unlock contact info
emkay.gg()            # good game

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Portfolio

Function
emkay.whoami()	# Bio card — name, role, availability
emkay.summary()	# Terminal resume — full snapshot
emkay.pitch()	# 30-second elevator pitch
emkay.hire_me()	# Why hire emkay
emkay.contact()	# Email, phone, GitHub, LinkedIn

Projects

Function
emkay.projects()	# All projects as DataFrame
emkay.projects(role='MLE')	# Filter by role tag
emkay.projects(domain='audio')	# Filter by domain keyword
emkay.projects(stack='XGBoost')	# Filter by tech
emkay.projects(sort='year', asc=True)	# Sort ascending
emkay.project('tacoma')	# Full case study
emkay.project('tacoma', mode='short')	# One-liner summary
emkay.project('tacoma', mode='json')	# Raw dict
emkay.top(n=3)	# Most recent n projects
emkay.random()	# Random project
emkay.search('CNN')	# Search across all fields
emkay.shap('tacoma')	# SHAP feature importance chart

Skills & Background

Function
emkay.skills()	# Skill proficiency bar chart
emkay.stack()	# All technologies used
emkay.domains()	# All project domains
emkay.education()	# Degrees and GPA
emkay.achievements()	# Awards, leadership, distinctions
emkay.learning()	# Currently learning

Export & Resume

Function
emkay.resume()	# Full text resume in terminal
emkay.resume(open=True)	# Text resume + opens emkaymoin.com
emkay.export('json')	# Export full portfolio as JSON
emkay.export('txt')	# Export full portfolio as text file

Easter Eggs

Function
emkay.origin()	# The story of how emkay became a data scientist
emkay.loadout()	# Tech stack as a gaming loadout
emkay.bgmi()	# Esports career and what it taught about data science
emkay.rubiks()	# ASCII Rubik's cube and the cube story
emkay.fun_fact()	# Random fun fact about emkay
emkay.puzzle()	# Solve a data riddle to unlock contact info
emkay.solve('your answer')	# Submit your puzzle answer
emkay.gg()	# Good game — closing message

Meta

Function
emkay.roast()	# Random roast — self, recruiter, or tech person
emkay.version()	# Package version and changelog
emkay.changelog()	# Alias for version()
emkay.star()	# GitHub repo link
emkay.credits()	# End credits screen
emkay.timeline()	# ASCII project timeline
emkay.help()	# All commands

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Projects

Year	Title	Domain	Key Result
2026	Tacoma Pole Inspection Risk	Utilities · ML	18% est. risk ↓
2026	SafeANC — Emergency-Aware ANC	Audio AI · DL	Concept · <50ms target
2026	Legal Clause Classifier	NLP · DL	87% F1
2025	Bird Species Audio Classification	Audio · DL	100% binary · 71.9% multiclass
2025	Youth Substance Use Risk	Health · ML	81% accuracy
2025	Global Mortality Analysis	Health · Research	75–80% variance explained
2024	Seattle Smart Parking Demand	ML · Geospatial	R² = 0.86
2024	SVM-Based Diabetes Risk Prediction	Health · ML	84% accuracy · ROC-AUC 0.91

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Zero dependencies

emkaymoin works out of the box with no required dependencies. If pandas is installed, emkay.projects() returns a DataFrame. If not, it prints a clean text list. Either way it works.

pip install emkaymoin           # zero dependencies
pip install emkaymoin[full]     # with pandas

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Contact

• 📧 [e-mail]
• 🔗 linkedin.com/in/emkaymoin
• 🐙 github.com/kmohammedsu
• 🌐 emkaymoin.com

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Data Scientist · M.S. Data Science · Seattle University · June 2026 · Available full-time