Tools

Ohhh. You wanted a clean, copy-pasteable text list. Not a sarcastic cyber-wall of doom. Fine. Here's everything you need to build and support all your QuantML modules, in simple list format like you're packing a tech suitcase for a finance startup.

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✅ Tools & Technologies Needed for QuantML

🐍 Programming & Core Libraries

• Python 3.x

• pandas

• numpy

• openpyxl

• python-pptx

• schedule

• os, glob, pathlib

• requests

• json

📊 Data Visualization

• matplotlib

• seaborn

• plotly (optional)

🧪 Machine Learning & Forecasting

• scikit-learn

• xgboost

• prophet

• statsmodels

• joblib (for saving models)

🤖 Generative AI / GPT Integration

• openai

• langchain (optional)

• transformers (optional/advanced)

🧰 Automation & Reporting

• openpyxl (Excel automation)

• python-docx (optional for Word docs)

• python-pptx (PowerPoint automation)

• smtplib / yagmail (email automation)

🌐 Dashboarding / Web Apps

• streamlit

• gradio (optional)

• dash (optional)

🧾 Data Sources & APIs

• yfinance

• nsetools

• beautifulsoup4 (for web scraping)

• newsapi.org (optional for news sentiment)

• selenium (for complex scraping tasks)

📤 Deployment / Hosting

• Streamlit Cloud

• Hugging Face Spaces

• Render

• Heroku (limited free tier)

• Vercel (if you want React stuff)

📁 BI & ERP Integration

• Excel exports from:

  • Oracle

  • SAP

  • NetSuite

• Tableau / Power BI connector exports

• csv, xlsx, xml file parsing in Python

🧠 Extra Tools (Optional but Powerful)

• sqlite3 / SQLAlchemy (simple databases)

• duckdb (in-memory analytics)

• weasyprint (for PDF generation)

• watchdog (for real-time folder triggers)

• cron / Windows Task Scheduler (script automation)

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💡 Skills Required

🐍 Python Fundamentals

• Variables, loops, functions, data structures

• File handling, error handling

• Working with APIs (requests, headers, JSON)

📊 Data Analysis

• Excel and CSV handling

• Time series manipulation

• Financial ratios, KPIs, variance reporting

🤖 ML & GPT Skills

• Supervised & unsupervised learning basics

• Model evaluation (RMSE, MAE, AUC, F1)

• Prompt engineering for GPT

• Connecting GPT to dataframes and outputs

📈 Visualization & Dashboards

• Chart building

• Streamlit interface design

• Exporting dashboards as Excel/PDF

🧾 Financial Reporting Skills

• P&L, Balance Sheet, Cash Flow structure

• Budget vs Forecast logic

• Commentary writing (GPT-enhanced or otherwise)

🌐 Dev & Deployment

• Git + GitHub

• Environment setup (venv, pip, requirements.txt)

• Deploying Streamlit apps

• Managing API keys and config files