AI Made Simple
FreqAI Needs a Data Scientist.
We Just Need Your Trading Idea.
FreqAI integrates machine learning into Freqtrade — but requires understanding of feature engineering, model training, scikit-learn, and GPU setup. The cryptorobot.ai AI agents build strategies from plain English.
The Problem
What You Deal With Today
ML Expertise Required
FreqAI requires understanding of feature engineering, model selection (LightGBM, XGBoost, CatBoost), and training pipelines.
Heavy Compute Needs
Training ML models requires significant RAM and CPU/GPU. A standard VPS cannot handle it effectively.
Feature Engineering
You must manually define feature sets, training windows, and label targets in Python. Poor features = poor predictions.
Side-by-Side
Feature Comparison
| Capability | Freqtrade | cryptorobot.ai |
|---|---|---|
| AI strategy creation | Write Python ML pipeline | Describe in plain English |
| ML knowledge required | Extensive (features, models, tuning) | None — AI handles it |
| Compute for training | Local CPU/GPU (hours) | Cloud HPC (minutes) |
| Model management | Manual file-based | Automatic versioning |
FAQ
Frequently Asked Questions
What is FreqAI?
FreqAI is the Freqtrade machine learning module. It lets you train prediction models (LightGBM, XGBoost, etc.) on market data to generate trading signals.
Do I need ML experience for AI trading?
With FreqAI, yes. With cryptorobot.ai, no — describe your strategy in plain English and our AI agents handle the rest.
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AI Trading Without the PhD.
Describe your strategy idea. Our AI builds, tests, and optimizes it for you.