BlackShelf Analytics

Welcome to BlackShelf Analytics, a portfolio of data-science projects and interactive visualisations built with Flask, Python, and D3.js.

Projects

1. Forecasting Eaches

A long-term LSTM model predicting daily warehouse volume based on:

  • Historical sales
  • Temperature trends
  • Promotional intensity

“The goal isn’t to predict the future perfectly — just to make tomorrow less of a surprise.”

2. Graph Visualiser

An interactive graph tool built with D3.js:

  • Add, remove, and connect nodes
  • Supports multiple links between the same nodes
  • Uses a spring layout for optimal spacing

Graph Preview

Technologies

Category Stack
Backend Flask, Python
Frontend HTML, Tailwind, D3.js
ML / Stats NumPy, Pandas, Scikit-Learn, TensorFlow
Deployment Docker, Google App Engine

Roadmap

  • [x] Build Flask app
  • [x] Dockerise for easy deployment
  • [ ] Add authentication and user dashboards
  • [ ] Integrate with BigQuery for live warehouse data

Contact

Attila Reinhart
attila@blackshelf.io
blackshelf.io

“Data is only useful when it tells a story worth listening to.”

Example with Code and Math

Below is a Python function:

import math

def f(x):
    return math.exp(-x) * math.cos(2*x)

$$ f(x) = e^{-x} \cos(2x) $$

Example: Hidden Section

Here’s a collapsible explanation:

Click to expand detailed notes This section is **hidden by default**. You can include *Markdown*, **code**, lists, even images: 
def f(x):
    return math.exp(-x) * math.cos(2*x)

Bar chart