# DeAI Day Speaking Script (~5 min)

## Slide 0: Title (15 sec)

Hey everyone, I'm Jason from CrowdCent. Today we're going to build a crypto ranking model together and submit it live to our hyperliquid-ranking challenge. By the end of this session, you'll have a working submission predicting which Hyperliquid perps will outperform over the next 10 and 30 days.

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## Slide 1: Why CrowdCent? (45 sec)

So what is CrowdCent? We're building an open platform where data scientists can contribute predictions to a meta-model's trading signal, with the goal of ultimately scaling how we trade that signal.

In our first version, you predict 10-day and 30-day relative returns for crypto perpetuals on Hyperliquid. Your predictions get scored against reality, you earn points. So far we've distributed over $20K in USDC and NMR so far.

We currently have about 30 active participants with over 7,500 submissions. And we practice what we preach - we're scikit-learn experts and Numerai grandmasters ourselves.

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## Slide 2: How We're Different (60 sec)

We also have a broader mission of "decentralizing investment management." So we also run a hedge fund called SumZero Capital. That's why you'll hear me talk about blending quant signals with fundamental analysis.

On the fundamental side, we have analysts posting investment theses. We use NLP to extract signals from that research. On the quant side - that's you - we're crowdsourcing ML predictions.

**Today's workshop focuses purely on the quant/ML side** - the crypto challenge. But eventually, we're going to launch a Kaggle-style competition for the fundamental data too. Imagine predicting stock returns using both NLP-extracted thesis signals AND traditional quant features. That's where we're headed.

Everything we build is open source - the client library, the MCP tools for AI agents, even the portfolio rebalancing tools. We believe in positive-sum collaboration.

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## Slide 3: How Scoring Works (45 sec)

Two metrics matter for how we deploy capital in the hyperliquid-ranking competition:

**Spearman correlation** asks "is your overall ranking correct?" It treats all positions equally.

**NDCG@40** asks "are your TOP picks correct?" This matters more for trading because we're going to overweight your highest conviction calls.

If you nail the top and bottom of your rankings, you'll score well on NDCG even if the middle is messy. That's the edge that drives real returns.

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## Slide 4: What We're Building Today (45 sec)

Here's the architecture. We're pulling data from three sources:

- **CrowdCent** gives you 80 time-aware features plus the two targets
- **Numerai Crypto** adds 22 features from their v2.0 dataset
- **YIEDL** contributes over 3,600 features - DeFi metrics, sentiment, on-chain data

That's nearly 4,000 features total. We'll merge them, run feature selection to cut that down, train XGBoost, Random Forest, and LSTM models, then ensemble them together.

Note: this is pure quant - no fundamental NLP data in this challenge yet. That's coming later.

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## Slide 5: What You're Building Tomorrow (20 sec)

After today, you can level up: use our MCP server to let AI agents manage your workflow, have LLMs optimize your models, or even auto-trade the meta-model on Hyperliquid with cc-liquid.

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## Slides 6-7: GPU Setup (30 sec)

We've partnered with Yotta Labs to make this easy. Go to the template link, click Deploy, pick a GPU, and you'll have a JupyterLab environment pre-loaded with all the code and data. Takes about 2 minutes. You can also always bring the docker image locally and put it in Cursor or Claude Code.

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## Slide 8: sklearn Pipelines (20 sec)

Quick note on why we use sklearn pipelines: they're fully composable. You can swap out any component - different feature selector, different model - and everything just works. This is how you iterate fast.

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## Slide 9: Let's Build It (15 sec)

Alright, let's do it. Open the notebook, follow along, customize as you go, and we'll submit live by the end of the session.

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## Slide 10: Resources (15 sec)

All the links are here - GitHub, docs, Discord. Come say hi, ask questions, share what you build. Let's get started.

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