Develop an automated LightGBM (XGboost) Model in Python
Budget: $30 – $250 USD
This will be a long project that could take 1-2 months, you can almost view it as a small research project. I am a professor at NYU, and at the end of the project, I will send you a letter to say that you have been my research assistant on this reseearch project for two months from 2021 September, to 2022 November.
Perhaps you have heard of AutoML models, the idea is that we want to develop a method that would automatically create features (feature engineering), and hyperparameter tuning. What makes it easy in this project is that we already know what model we will use, and that is a lightGBM model.
The entire pipeline would involve preprocessing, feature engineering, feature selection, and then finally hyperparameter tuning. There are many solutions on GitHub that would help us develop this.
Perhaps you have heard of AutoML models, the idea is that we want to develop a method that would automatically create features (feature engineering), and hyperparameter tuning. What makes it easy in this project is that we already know what model we will use, and that is a lightGBM model.
The entire pipeline would involve preprocessing, feature engineering, feature selection, and then finally hyperparameter tuning. There are many solutions on GitHub that would help us develop this.
Related categories:
Python
Financial Research
Machine Learning (ML)
C++ Programming
Software Development