LSTM-RNN-CNN Projects
AI & Data Science --- Cloud-Deployed Crypto Forecasting Platform (ML & DL Based)
Crypto-Momentum Dashboard & Chatbot
Role • AI / Data Engineer & Full-Stack Dev Stack : Python · LightGBM · TensorFlow / Keras · Streamlit · yfinance · SHAP · Parquet/CSV
🚀 Professional Impact
| Metric | Outcome |
|---|---|
| Live Price Signals | Streaming LightGBM & LSTM predictions for BTC/ETH (+2 % moves, 1-/3-/5-day horizons) displayed in <150 ms on Streamlit. |
| Walk-Forward Backtest | Theoretical strategy outperforms buy-and-hold in high-volatility windows (2018 – 2023) with risk-adjusted gains illustrated on equity-curve. |
| Explainability | SHAP summary / waterfall plots expose top 10 lag & sentiment features → faster feature-engineering iterations. |
| Deployment Footprint | Single-page Streamlit app runs on free tier (Render) — no GPU; daily cron updates via GitHub Actions. |
🔧 Core Technical Highlights
| Domain | Implementation Details |
|---|---|
| Data Engineering | Daily OHLCV (2018-2025) via yfinance → Parquet; aggregated sentiment (news + social, last update May 2025). |
| Feature Pipeline | Lagged returns, rolling stats, TA-Lib indicators; stored with version tags for reproducibility. |
| ML Layer | LightGBM classifier (binary: +2 %) with joblib persistence; walk-forward split script auto-re-trains on latest window. |
| DL Layer | Single- & multi-task LSTM; experimental 1-D CNN benchmarked (lower F1, not promoted). |
| Explainability | SHAP KernelExplainer for LightGBM; plots cached to avoid recompute. |
| Dashboard | Streamlit + Plotly heatmaps, confusion matrices, equity curves; real-time prediction endpoint. |
| Planned Chatbot | FastAPI wrapper • Azure OpenAI / HF Transformers • vector store for Q&A on model outputs. |
🗂️ Feature Deep-Dive
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Interactive Dashboard – Toggle between ML & DL models; auto-refresh every 10 s.
-
Strategy Simulator – Capital allocation vs. buy-and-hold; CSV export for further analysis.
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SHAP Explorer – Drill-down feature importance by date-range and horizon.
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Road-map – Real-time NLP sentiment and LLM chatbot slated for v2.0.
🛠️ Challenges & Solutions
| Challenge | Mitigation |
|---|---|
| Sentiment feed is static (May 2025) | Flagged in UI; pipeline placeholders ready for real-time API once quota secured. |
| HF / OpenAI cost exposure | Chatbot deferred; inference layer stubbed, budgeted for pay-as-you-go rollout. |
| Streamlit free-tier sleep | GitHub Actions cron ping keeps service warm / <60 s cold-start. |
| Large backtest windows | Parquet partitioning + incremental fit to keep memory under 2 GB. |
Crypto-Momentum Dashboard v1.0 proves that lean Python tooling plus targeted ML/DL can generate actionable crypto insights—ready to scale with live sentiment and LLM interaction in v2.