OProject Overview
At Datraxa, we built an advanced time series forecasting system that predicts future market trends across multiple industries.
It helps businesses plan ahead by analyzing past data and spotting hidden patterns.
From stock price movement to product demand cycles, this system uses machine learning to forecast what’s coming next — giving companies the insights they need to make smarter, faster decisions.
🔍 Key Features
- Trend Detection:
Detects upward and downward trends using moving averages, momentum indicators, and trendlines. - Seasonality Analysis:
Breaks down time series data to reveal recurring patterns, seasonal peaks, and slow periods. - Predictive Modeling:
Uses ARIMA, Prophet, and LSTM models for both short-term and long-term forecasting. - Anomaly Detection:
Flags unusual spikes, drops, or irregular market behavior for early response. - Backtesting & Validation:
Tests models using cross-validation and metrics like MAE, RMSE, and MAPE to ensure accuracy and reliability.
⚙️ Tools & Technologies
- Python
- Pandas
- Prophet
- ARIMA
- LSTM
- Seaborn
- Matplotlib
- TensorFlow
- Scikit-learn
- Jupyter Notebook
💼 Applications
- Stock Market Prediction:
Forecast stock trends and manage investment risks. - E-commerce Demand Planning:
Predict product demand and plan seasonal campaigns effectively. - Cryptocurrency Forecasting:
Anticipate crypto price volatility and optimize trading decisions. - Retail Trend Analysis:
Align inventory, marketing, and logistics with consumer trends.
📈 Visual Highlights
- Forecast plots showing predicted vs. actual performance
- Seasonality charts and trend heatmaps
- Model accuracy graphs with confidence intervals
- Anomaly timelines showing market outliers
🚀 Result & Impact
Our forecasting system achieved over 87% accuracy in multi-step trend predictions.
It enabled businesses to react faster to market changes, optimize stock levels, and capitalize on new opportunities before competitors.
Datraxa — Turning data into foresight for smarter business decisions.