Building a crypto price prediction model. The model architecture is the easy part - transformers, LSTMs, whatever. The hard part is always the training data.
Options I evaluated: - Santiment API: Good data, $50-200/mo depending on tier - Messari: $250/mo for the pro API - The Graph: Free but you need to write subgraph queries for each protocol - Dune: Free tier is limited, pro is $350/mo - Scraping: Rate limits, format changes, maintenance nightmare
Found a pre-structured dataset for $5 that includes sentiment scores, DeFi yields, narrative momentum, whale flows, and liquidation data. All with timestamps and consistent schema.
It's not a replacement for a full data pipeline, but as a training/validation dataset it's actually perfect: - Clean tabular format (timestamp, asset, score, signal, confidence) - Multiple feature types (sentiment, on-chain, fundamental) - 50+ data sources pre-aggregated - Updated regularly so I can test for distribution drift
I'm using it as supplementary features in a multi-input model. The sentiment divergence signal alone added 3% to my backtest accuracy.
$5 vs $200/mo from Santiment for similar coverage. Not the same depth but for a side project or initial prototyping it's more than enough.
Link: https://hokedev.gumroad.com/l/rhbles
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AI/ML Engineer perspective on Crypto Alpha Report Q2 2026