https://github.com/sohomm/predict-insurance-charges

A predictive model to estimate the insurance charges based on a client's attributes, such as age and health factors. It offers a practical application of ml in business, enabling more accurate pricing models and helping companies manage risk while delivering personalized pricing strategies to clients.
https://github.com/sohomm/predict-insurance-charges

administration algorithm bot data decision-trees download easy finance github java machine-learning management model neural-network nlp prediction project science trading university

Last synced: 12 days ago
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A predictive model to estimate the insurance charges based on a client's attributes, such as age and health factors. It offers a practical application of ml in business, enabling more accurate pricing models and helping companies manage risk while delivering personalized pricing strategies to clients.

• Host: GitHub
• URL: https://github.com/sohomm/predict-insurance-charges
• Owner: SohomM
• License: apache-2.0
• Created: 2024-12-27T10:05:32.000Z (15 days ago)
• Default Branch: main
• Last Pushed: 2024-12-27T10:06:10.000Z (15 days ago)
• Last Synced: 2024-12-27T11:18:44.188Z (15 days ago)
• Topics: administration, algorithm, bot, data, decision-trees, download, easy, finance, github, java, machine-learning, management, model, neural-network, nlp, prediction, project, science, trading, university
• Language: Jupyter Notebook
• Homepage:
• Size: 769 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
#### The main objective of this repo is idea generation! Some of these 'strategies' might not be appropriate for consumption ~~due to overfitting~~ (it's meant to be educational)

Dependencies: Numpy; Pandas; Matplotlib and Requests (for fetching Yahoo Finance data)

#### Difficulty

Moderate:

[ML Based Pairs Trading](DecisionTreeRegressors.ipynb) - A simple Machine Learning example, Decision Tree Regressors applied to the previous pair (also requires Scikit-Learn)

Basic:

[Long Only Pairs Trading](PairsTrading.ipynb) - A simple pairs trading strategy focused on buying the loser! Signal is given by rolling correlation

Introductory:

[Dynamic Asset Allocation & Diversification](AssetAllocation.ipynb) - Exploring geographical diversification and optimizing capital allocation (also requires Scipy)

Market data last updated at 2 July 2020

#### License

This code has been released under the [Apache 2.0 License](LICENSE)