- 👋 Hi, I’m @minye
- 👀 I’m interested in data science and blockchain technologies:
- data science from Machine Learning, related cloud engineering and from business perspectives
- blockchain technologies with a focus on smart contracts - and I love drawing, so also interested in NFTs
- 🌱 I’m currently learning about blockchain and smart contracts.
- 💞️ I’m looking to collaborate on projects related to:
- data science: I bring experience in the areas of (data science in) biomedicine, legal tech, IoT.
- web3: learning about smart contracts and love drawing myself
- 📫 How to reach me: feel free to drop me an email to minye.epfl@gmail.com
This repository is dedicated to give first inspirations on how to tackle general business use cases, each folder denotes one use case.
The folder "churn_prediction" depicts the general concept of how to tackle a problem of 'customer churn prediction'. The dataset used in this repository is the KAGGLE dataset for "churn for bank customers": https://www.kaggle.com/datasets/mathchi/churn-for-bank-customers .
As all complete data science projects, it comprises the following parts:
- business and data understanding
- exploratory data analysis (EDA)
- data preparation
- modeling
- model evaluation
Please, beware that in real-world scenarios, these parts are undergone iteratively before a model is deployed. And after such model deployment, the maintenance and updating of the model also needs such continuous iterations.