Using Bayesian Regime Detection to Read Stock Market States
A Practical Regime Filter for Stock ResearchContinue reading on Towards AI »
ai, bayesian-statistics, Machine Learning, python, stock-market
ai, hidden-markov-models, Machine Learning, python, stock-market
Using Hidden Markov Models to Read Stock Market Regimes
Why I Use HMM as a Stock Research ToolContinue reading on Towards AI »
ai, competition, economics, Model, specialization
AI Does Not End Competition. It Changes the Geometry of Competition
A model for how AI pushes economies from shortage to specializationContinue reading on Towards AI »
decision-making, Machine Learning, predictions, reinforcement-learning, timeseries-forecasting
From Prediction to Action: Why Enterprise AI Needs Supervised Learning, Time-Series Thinking, and…
How Forecast Updating, Drift Adaptation, and Sequential Decision Thinking Are Reshaping Business AIContinue reading on Towards AI »
algorithms, business, Machine Learning, python, reinforcement-learning
Group-Relative Contextual Bandit Policy Gradient for Homepage Recommendation
Efficient Reinforcement Learning from Relative Slate Quality in Contextual BanditsContinue reading on Towards AI »
ai, algorithms, quantitative-finance, random, stock-market
Gap-Up and Fade Is Not Random
A Quantitative AI Framework for Identifying Stocks Prone to Overnight Strength and Intraday ReversalContinue reading on Towards AI »
ai, forecasting, python, reinforcement-learning, timeseries
Time Series Forecasting Changes When Actions Change the Data
A practical framework for action-aware forecasting in business and investingContinue reading on Towards AI »
ai-agent, first-principles, python, rags, rlhf
What SFT, DPO, RLHF, and RAG Actually Do in an AI Agent
A first-principles guide for AI agent builders — understand how demonstration learning, retrieval, preference optimization, and…Continue reading on Towards AI »
data, decision-making, exploitation, exploration, reinforcement-learning
Exploration and Exploitation: The Simple Yet Profound Logic at the Heart of Reinforcement Learning
Why every smart system — and every smart person — must learn to balance “trying new things” with “sticking to what works”Continue reading on Towards AI »