The Library
Omega Makena Mwebia
Quantitative researcher, machine learning engineer, and independent researcher behind Scarcity.
Omega Makena Mwebia
Quantitative researcher, machine learning engineer, and independent researcher behind Scarcity.
Models & Systems
I build quantitative and machine-learning models for complex, data-constrained problems.
Structure Before Scale
I look for the relationships and structure within a system before relying on more data, larger models, or more computation.
Understand the System
I want to understand how complex systems behave, interact, and change—not just predict their next output.
Explanations & Teaching
Concepts and reference guides grouped by paradigm and foundations.
Foundations
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What is Big Data?
An accessible introduction to big data, its characteristics, and its impact on modern technology and business.
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AI Research in First vs. Second & Third World Countries - A Growing Divide
Exploring the growing divide in AI research capabilities between developed and developing countries, and its implications.
Learning Paradigms
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Federated Learning - What It Is, Approaches, Algorithms, and How to Train One
A comprehensive guide to Federated Learning, covering its approaches, algorithms, training process, and practical applications in privacy-preserving machine learning.
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Meta-Learning - Learning How to Learn
Exploring meta-learning as an approach to teaching models how to learn, with practical insights from building KShield and continuous adaptation systems.
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How I Ended Up Learning Federated Learning the Hard Way
My journey into federated learning while building a macroeconomic simulation model, and how it solved my impossible data problem.
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Mixture of Experts - Scaling AI by Specialization
Exploring how mixture of experts architectures enable more efficient and scalable machine learning systems.
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Meta-Learning and Adaptation - Learning to Learn Faster
How meta-learning enables AI systems to rapidly adapt to new tasks with minimal data.
Systems Thinking
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Review of "A Path Towards Autonomous Machine Learning Intelligence" by Yann LeCun
A comprehensive analysis of Yann LeCun's vision for autonomous machine learning and the future of AI systems.
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Forecasting GDP Growth with Machine Learning
Applying time series forecasting and ML techniques to predict economic growth indicators.
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Review of "ABIDES-Economist - Agent-Based Simulation of Economic Systems with Learning Agents"
An analysis of ABIDES-Economist, a framework for agent-based economic simulation using machine learning agents.
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Building AI Agent Architecture - The House Analogy
Designing AI agent architecture through a house analogy - foundation, pillars, roof, and refurbishing for practical deployment.
Practical Advice
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Object-Oriented Programming in Machine Learning
Exploring how object-oriented programming principles enhance machine learning development and code organization.
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Why Your Self-Driving Car Needs Fake Rain (and Other AI Secrets)
Exploring synthetic data generation as a solution to overcome data scarcity in AI systems, particularly in autonomous vehicles.