ml-for-finance

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ml-for-finance 최신버젼 다운로드

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# 12‑Week ML for Finance Self‑Study Roadmap

**Transforming theory into publishable research & real‑world finance models**  
I’m on a 12‑week sprint—60–80 hrs/week—building theory, replication studies, and an original ML‑for‑finance project. I’ll post daily progress updates, insights, failures, and wins on LinkedIn and X to grow a community, get feedback from advisors, and catch the eye of quant firms.

---

## 🚀 Why Follow Along?
- **Real‑time learning**: See how I tackle proofs, implement papers, debug models, and iterate.  
- **Networking & feedback**: Drop comments or DMs on LinkedIn/X to guide me or suggest papers.  
- **Career signal**: Quant firms, research labs, and PhD advisors—watch my journey and reach out if you see fit.

---

## 📅 Weekly Roadmap (High‑Level)
| Week | Focus                                    | Deliverable                                             |
|------|------------------------------------------|---------------------------------------------------------|
| 1    | Foundations & linear regression          | 10 proofs (PDF), regression notebook, LaTeX summary     |
| 2    | Deep learning & optimization             | Adam derivation, batch‑norm code, MLP ablation study    |
| 3    | Probabilistic models & BNNs              | ELBO proofs, BNN notebook, project outline              |
| 4    | RNNs/LSTMs for time series               | LSTM derivation, Greff summary, HFT signal notebook     |
| 5    | Transformers & attention                 | Attention math, transformer notebook, baseline metrics  |
| 6    | Reinforcement learning                   | Policy‑gradient proofs, DQN notebook                    |
| 7    | Graph Neural Networks                    | GCN derivation, GCN notebook, risk modeling results     |
| 8    | Adversarial robustness                   | FGSM/PGD derivations, adversarial training notebook     |
| 9    | Generative models (GANs)                 | GAN derivation, GAN notebook, synthetic trajectory vis  |
| 10   | Hybrid models & paper drafting           | Black‑Litterman math, hybrid model notebook, draft intro|
| 11   | Polish portfolio & paper                 | Complete derivations anthology, polished repo, draft    |
| 12   | Submission & outreach                    | Final paper, slides, blog posts, emails to advisors     |

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## 🗂️ Repo Structure

proofs/              # Pen‑and‑paper derivations (PDF + .tex)
summaries/           # 1‑page LaTeX paper notes
notebooks/           # Jupyter notebooks (replications + project)
paper/               # Final paper draft (LaTeX)
slides/              # Beamer slide deck for 5‑min talk
blog/                # Markdown blog posts (for GitHub Pages)
README.md            # This file

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## 🔧 How to Get Started

1. **Clone this repo**  
   ```bash
   git clone https://github.com/maestroK/ml-for-finance.git
   cd ml-for-finance
___

#### Run & iterate  
Python 3.10+, PyTorch, JAX, Pyro, pandas installed  
Launch notebooks in your environment  
Follow my daily updates  
**LinkedIn**: [linkedin.com/in/abdul-samad-khan-1727b41b3](https://www.linkedin.com/in/abdul-samad-khan-1727b41b3)  
**X (Twitter)**: [@abdul_sama87267](https://x.com/abdul_sama87267)

---

### 🤝 Let’s Connect

**Feedback & questions**: Comment on LinkedIn/X or open an issue in this repo.  
**Advisors & collaborators**: DM me to co‑author or guide the project.  
**Quant firms & recruiters**: Watch my public repo and reach out if you see potential fit.

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