We're building a platform for data scientists to predict performance using multi-modal embeddings of investment analyses.
import crowdcent_challenge as cc
# Challenge status
print(cc.status())
# Output: "Challenge launching soon. Stay tuned!"
# What to expect
features = [
"Investment research embeddings",
"Financial metrics",
"Market context data"
]
for feature in features:
print(f"- {feature}")Create novel ML architectures that process multi-modal data
Surface predictive signals from complex financial datasets
Compete & share insights with quant researchers worldwide