pingao2019/class_test

Here is me: 👋

• 🔭 I’m currently working on Data Science.
• 👯 I’m looking to collaborate on Data Science,
• 🤔 My skills: Statistics, Predictive Modeling, Data Engineering, Machine Learning, Computer Science.
• 📫 How to reach me: https://medium.com/@papython2019
• 😄 Fun facts: travel, read, music, cook, garden, and so on.
• ⚡ My projects:

1. Bridges to Prosperity
   Bridges to Prosperity is a project that helps to build footbridges in Rwanda isolated area. Cross-collaborate with web developers and other data scientists. Collect data. Clean and mine data. Create prediction model and make API. Learned how to design a project and how to make the wireframe. Learned engineering architecture and engineering critique on architecture and code bases. Practiced using Github and setting goals and processing the project by Trello board. Learned not only technical skills, also learned communication skills and how to work as a team with people having different backgrounds and personalities.Link: https://github.com/Lambda-School-Labs/Labs25-ds

2. Med Cabinet Cross-collaborate with web developers and other data scientists to let the user query with strain data along a machine learning model to guide user recommendations. Link: https://github.com/bw-med-cabinet/DS-4

3. Using python to code K-Means Clustering Algorithm( May 2020 ) Try to further explore K-Means Clustering Algorithm with mathematics behind and also by using python to code K-Means Clustering and comparing with the edition of Sklearn Library to grasp the most common clustering skill. Blog: https://medium.com/@papython2019/k-means-cluster-6958a9739d75

4. Prediction of Salary Dased on BLS Data To predict wages by using machine learning to fit regression models on the dataset and evaluate the accuracy of the models by obtaining Mae and/or R². Blog: https://medium.com/@papython2019/predicting-salary-with-bls-2019-dataset-84bf947d35e3. Portfolio: https://github.com/pingao2019/Salary-Prediction-Portfolio

5. To make a model to diagnose diabetes To identify trends and relationships and use visualization and by build a correlation coefficients matrix to make diabetes diagnosis prediction and draw appropriate conclusions. Blog: https://medium.com/@papython2019/some-facts-about-diabetes-eb0b160277e9