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ds_academic_papers's Introduction

Code for the DS blog

Description: code walkthroughs that are used in my personal data science blog. The blog looks to bring academic research to the DS industry. If you have any comments/questions/ideas, feel free to reach out here. Also use any code here if you'd like

Date: 2021-2022

Files

  • 22_time_series_cleaning_and_clustering.py: walkthrough of how to perform feature based clustering on time series data. There are also resources linked in the file for distance-based clustering using DTW.
  • 28_prophet_vs_neural_prophet.py: comparison between Facebook's Prohpet and NeuralProphet packages on energy consumption data in California.
  • 32_freaai_potential_implementation.py: potential implementation of IBM's FreaAI for finding weak data slices for a binary classifier. This project has lots of potential, but the code is not very usable as of now.

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