Guides, comparisons, and deep dives on AI trading bots.
Transform raw OHLCV candles into features an AI model can learn from. Build a complete feature pipeline: returns, moving averages, volatility, volume analysis, and RSI. Understand why feature quality matters more than algorithm choice.
Walk through every line of bot.py. Learn what ccxt does, how the prediction loop works, and how to tweak trading pairs, timeframes, and confidence thresholds. No Python experience needed.
Buy a $5 VPS, SSH in, install Python, clone your AI trading bot, and watch it print live BTC predictions. Part 2 of the 10-part build series - your first working bot, no coding required.
From VPS to API to AI-driven execution - follow one trade through your future bot's pipeline. First in a 10-part series: build your own AI trading bot from scratch, no coding experience required.
Backtest results are marketing. Paper trading is step one. Here's how to actually evaluate an AI model before it touches your capital - distribution shift, retrain verification, walk-forward gaps, and model drift.
How to evaluate AI trading bots: ML vs rule-based strategies, signal bots vs execution bots, pricing tiers, and a beginner checklist. Includes concrete recommendations and an FAQ.