BSc Computer Science student at JKUAT (Nairobi, Kenya) specializing in building end-to-end Machine Learning pipelines, scikit-learn models, and scalable full-stack applications. Driven by practical impact: 70% hands-on building, 30% theory.
Passionate about extracting actionable insights from data and architecting intelligent software systems that deliver real value.
I am a Computer Science undergraduate with a deep focus on Machine Learning and Data Science. Rather than just memorizing theoretical algorithms, my development methodology centers on building end-to-end pipelines: from rigorous exploratory data analysis (EDA) and feature engineering to model regularization and deployment.
I complement my ML expertise with strong full-stack foundations in Python (Django, Flask) and TypeScript/React. This dual perspective ensures the models I construct aren't just isolated Jupyter notebooks—they are ready to be served, containerized, and integrated into live user-facing applications.
class Lampard:
name = "Lampard Kipyegon"
location = "Nairobi, Kenya"
education = "BSc Computer Science (JKUAT)"
primary_focus = [
"Machine Learning",
"Data Science",
"Full-Stack Development"
]
current_mission = (
"Building leakage-free ML pipelines "
"with scikit-learn & Python"
)
principles = ["70% practice, 30% theory", "Clean abstractions"]
interests = ["Chess", "Open source", "Predictive modeling"]
def say_hi(self):
return "Let's build something intelligent together."Curated tooling stack focused on modern machine learning workflows, statistical data processing, and full-stack web software.
Real-world applications and model implementations from my GitHub workspace.
Structured 12-week machine learning curriculum repository covering regression, classification, exploratory data analysis, and leakage-free preprocessing with scikit-learn Pipeline and ColumnTransformer.
An active laboratory of applied machine learning models, statistical experiments, and data science workflows. Currently testing predictive models and model evaluation benchmarks.
A full-stack bookstore web application developed using Django and Firebase backend. Includes catalog browsing, secure user authentication, order handling, and persistent data storage.
Analytical TypeScript web application built with strict typing and clean modular architecture, designed for intuitive data presentation and responsive user interaction.
Competitive hackathon codebase developed at university. Built under rapid prototyping constraints to deliver functional, high-quality full-stack software.
Daily journaling and reflection interface engineered with TypeScript, featuring smooth UI micro-interactions and structured local state management.
Interested in collaborating on Machine Learning projects, engineering roles, or discussing software? Reach out directly below.
I am actively open to Machine Learning and Software Engineering opportunities, internships, and research collaborations. Drop me a note and I will get back to you promptly.