SZEL https://validator.w3.org/feed/docs/rss2.html Environment Setup and Data Collection Home Building Confidence Intervals Lesson 1 Model Accuracy Data Splitting NBA Play-by-Play Models for Prediction Markets (Level 2) NBA Play-by-Play Models for Prediction Markets (Level 1) How to Optimally Size Positions How to Stop Missing Fills How to Stop Overpaying for Contracts Exposure Management Trade Flow Analysis Order Book Imbalance Trade Entry Signals Position Sizing Spread & Slippage Codebase setup and overview Lesson 2 API utilities and local database setup Create virtual environment, install requirements Scaling Up — and Knowing When to Pull Back Building Automated Stop-Loss Systems Smarter Trade Entries Managing Total Risk Across Multiple Games Sizing Your Trades for Maximum Growth Execution & Liquidity Modeling Edge Filtering & Calibration Team Histories & Matchups Basic Models Advanced Models Working with Kalshi’s API Capturing Current Game State Time-Based Features Model vs Market Probabilities Training Graph Neural Networks Working with Sports Data APIs Use Graph Embeddings in Any Model Building the NBA Interaction Graph Pretraining & Transfer Learning Learning Team & Player Embeddings Adding guardrails for smart trading Creating a trading bot Working with Kalshi websockets for live data Understanding Kalshi’s API Checkout WebSocket Streaming Cart Instructor Registration Event-Driven Bot Design