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Exploring enzimes stability with clustering, ensemble, boosting and other ML methods! Flask app with NN to predict the target

Jupyter Notebook 42.40% Python 0.87% PureBasic 0.28% HTML 56.46%

eda enzime flask knn ml neural-network python random-forest visualization xgboost

bauman-mgtu-capstone's Introduction

Hi here ✨ I am Luca

🚀 Let's collaborate: I am interested in Data Science and application of ML and AI in social sciences and AI for Good.
👩🏻‍💻 Work: Currently, I am working in the MIPT — Moscow Institute of Physics and Technology - in the Marketing domain.

🧮Tech Stack

🐍: pandas, numpy, VIZ: matplotlib, seaborn, plotly, folium, ML: sklearn, tensorflow; WebApp: Flask
R
SQL
HTML, CSS
Google Analytics
Zignal Labs
Git, Github
Linux
Spark

🎶 Contacts

Telegram: @lucaostra
Email: [email protected]
Website: https://lucaostra.github.io/o
Kaggle: https://www.kaggle.com/olgashevtsova

⬇️ And check out my DS projetcs below in the repo ⬇️

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