Feature Request: Add a Section to Visualize and Train TimeSeries Forecasting Data

[HARSHITA005-GARG]

Hi @manasvi-0,
I had an idea to add a Section to Visualize and Train TimeSeries Forecasting Data to enhance the learning experience on AlgoLab. I believe this could be a valuable addition to the project.
Looking forward to hearing your thoughts and discussing it further!

🚀 Feature Proposal: Add Time Series Forecasting Dataset, Visualization & Model Training

📌 Summary

I propose adding Time Series Forecasting capabilities to the AlgoLab project by integrating a suitable dataset, creating visualizations, and training forecasting models. This will expand AlgoLab's scope beyond static datasets and demonstrate its capabilities in handling temporal data.

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🎯 Motivation

Currently, AlgoLab focuses primarily on classification, clustering, and regression tasks. Many real-world problems, however, involve time-dependent data such as:

• Stock market prices
• Weather patterns
• Energy consumption
• Sales trends

Adding Time Series Forecasting will:

• Showcase AlgoLab’s adaptability to different data types
• Help users understand forecasting workflows
• Provide an example for ML tasks involving temporal sequences

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🛠 Proposed Implementation

1. Dataset Acquisition

   • Use a publicly available dataset (e.g., from Kaggle or UCI ML Repository) or upload data using CSV Format
   • Possible choices:
     • Daily minimum temperatures (Australia)
     • Air passengers dataset
     • Electricity consumption dataset

2. Data Preprocessing

   • Parse date-time columns
   • Handle missing values
   • Aggregate/normalize data if needed

3. Visualization

   • Plot time series line charts
   • Show seasonal trends & moving averages
   • Highlight anomalies

4. Model Training

   • Implement baseline models (Naïve, Moving Average)
   • Integrate advanced models (ARIMA, Prophet, LSTM if feasible)
   • Evaluate using metrics like MAE, RMSE, MAPE
   • Enables users to hypertune and visualize the effects

5. Integration in AlgoLab

   • Add as a separate section/module under “Forecasting”
   • Provide notebook or interactive dashboard for exploration

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📊 Example Visuals (Concept)

(These will be implemented in the final PR)

• Trend Plot
  • A line chart showing data over time
• Seasonality Decomposition
  • Trend, seasonality, and residual components
• Forecast Plot
  • Historical data + predicted future values

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✅ Benefits

• Broadens AlgoLab’s problem coverage
• Provides a complete pipeline from data → visualization → model → evaluation
• Helps beginners learn time series forecasting techniques
• Encourages contributions in other temporal data tasks

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Would love to hear your thoughts on integrating this into AlgoLab!

[manasvi-0]

@HARSHITA005-GARG yes you can work on this after compeleting your task please raise a PR and dont merge it until i review it

[HARSHITA005-GARG]

@manasvi-0 please assign it to me and also add gssoc level to it

[manasvi-0]

@viv2005ek please assign him