Update README.md
Browse files
README.md
CHANGED
|
@@ -1,20 +1,49 @@
|
|
| 1 |
---
|
| 2 |
-
title: Workforce
|
| 3 |
-
emoji:
|
| 4 |
-
colorFrom:
|
| 5 |
-
colorTo:
|
| 6 |
-
sdk:
|
| 7 |
-
|
| 8 |
-
|
| 9 |
-
- streamlit
|
| 10 |
pinned: false
|
| 11 |
-
short_description: Workforce_Optimizer
|
| 12 |
-
license: apache-2.0
|
| 13 |
---
|
| 14 |
|
| 15 |
-
#
|
| 16 |
|
| 17 |
-
|
| 18 |
|
| 19 |
-
|
| 20 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
---
|
| 2 |
+
title: Workforce Optimization AI
|
| 3 |
+
emoji: 📞
|
| 4 |
+
colorFrom: blue
|
| 5 |
+
colorTo: green
|
| 6 |
+
sdk: streamlit
|
| 7 |
+
sdk_version: 1.31.0
|
| 8 |
+
app_file: app.py
|
|
|
|
| 9 |
pinned: false
|
|
|
|
|
|
|
| 10 |
---
|
| 11 |
|
| 12 |
+
# 📞 Workforce Optimization AI / İş Gücü Optimizasyonu
|
| 13 |
|
| 14 |
+
This project is an AI-driven decision support system designed to optimize staffing levels based on historical call/demand data. It uses Long Short-Term Memory (LSTM) networks to predict future demand and suggests actionable staffing strategies.
|
| 15 |
|
| 16 |
+
Bu proje, geçmiş çağrı/talep verilerine dayanarak personel seviyelerini optimize etmek için tasarlanmış yapay zeka destekli bir karar destek sistemidir. Gelecekteki talebi tahmin etmek için LSTM ağlarını kullanır ve uygulanabilir personel stratejileri önerir.
|
| 17 |
+
|
| 18 |
+
## 🚀 Features / Özellikler
|
| 19 |
+
|
| 20 |
+
- **AI Demand Forecasting:** Predicts future call volumes using deep learning.
|
| 21 |
+
- **Strategic Recommendations:** Automatically identifies "High Intensity" (Risk) and "Saving Area" (Opportunity) periods.
|
| 22 |
+
- **Cost Optimization:** Helps managers balance service quality and labor costs.
|
| 23 |
+
- **Interactive Visualization:** Dynamic charts showing demand vs. staff capacity.
|
| 24 |
+
|
| 25 |
+
## 🛠️ Tech Stack / Teknolojiler
|
| 26 |
+
|
| 27 |
+
- **Python** (Core Logic)
|
| 28 |
+
- **TensorFlow/Keras** (LSTM Model)
|
| 29 |
+
- **Streamlit** (Web Interface)
|
| 30 |
+
- **Plotly** (Interactive Graphics)
|
| 31 |
+
- **Scikit-Learn** (Data Scaling)
|
| 32 |
+
|
| 33 |
+
## 📖 How to Use / Nasıl Kullanılır?
|
| 34 |
+
|
| 35 |
+
1. **Upload Data:** Upload a CSV file containing a column named `calls`.
|
| 36 |
+
2. **Set Parameters:** Adjust hourly wage and staff capacity per hour from the sidebar.
|
| 37 |
+
3. **Analyze:** - View the **Decision Logic** to understand AI suggestions.
|
| 38 |
+
- Check the **Strategic Recommendations** for peak and low-demand periods.
|
| 39 |
+
- Download the **Detailed Schedule** for operational planning.
|
| 40 |
+
|
| 41 |
+
---
|
| 42 |
+
|
| 43 |
+
### 🧠 Strategic Logic / Stratejik Mantık
|
| 44 |
+
|
| 45 |
+
- **High Intensity (🔥):** When predicted demand exceeds capacity. Action: Increase staff to prevent customer loss.
|
| 46 |
+
- **Saving Area (💰):** When demand is significantly lower than capacity. Action: Reduce staff or plan breaks to minimize labor waste.
|
| 47 |
+
|
| 48 |
+
**Note:** Each "Slot" in the analysis represents a sequential row from your uploaded data (e.g., Slot 0 = 08:00 AM, Slot 1 = 09:00 AM).
|
| 49 |
+
---
|