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Anomaly Detection in Time Series #967
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Thank you for creating this issue! We'll look into it as soon as possible. Your contributions are highly appreciated! 😊 |
Assign me the task under GSSOC and HACKTOBERFEST @abhisheks008 |
??? |
Is the project ready with you? Can you make the PR as early as possible? If yes then make the pull request I will review and add the labels. |
yes its ready |
Make a pull request, I'll do the needful. |
REVIEW THE PR ASAP @abhisheks008 |
Deep Learning Simplified Repository
🔴 Project Title: Anomaly Detection in Time Series Using LSTM Networks
🔴 Aim: To develop an effective model for detecting anomalies in time series data, leveraging LSTM networks for improved accuracy and reliability.
🔴 Dataset: Synthetic Dataset
🔴 Approach: Implement 3-4 algorithms for anomaly detection, such as LSTM, Facebook Prophet Classification, and Isolation Forest. Conduct exploratory data analysis (EDA) to understand the data distribution and characteristics, and compare model performances using accuracy scores to identify the best-fitting model.
📍 Follow the Guidelines to Contribute in the Project:
Create a separate folder named as the Project Title.
Inside that folder, include:
requirements.txt
- List of required packages/libraries.In the
Model
folder, provide a comprehensiveREADME.md
with visualizations and conclusions.🔴🟡 Points to Note:
✅ To be Mentioned while taking the issue:
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎
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