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1. BERT-Fine-Tuning-and-AWS-Comprehend-for-Multi-label-Text-Classification BERT-Fine-Tuning-and-AWS-Comprehend-for-Multi-label-Text-Classification Public

   The web scraping code extracts detailed product information, forming the foundation for ML-based categorization. Two methods are implemented for assigning category tags to products based on their t…

   Jupyter Notebook 5

2. Car-Parts-Competitive-Analysis-NLP-Tableau-Clustering Car-Parts-Competitive-Analysis-NLP-Tableau-Clustering Public

   Applied NLP for automated categorization of products, aligning Amazon items with CARiD’s category framework. Conducted significant statistical analysis to unearth factors influencing product popula…

   Jupyter Notebook 2

3. Fetal-Health-Classification-with-Pyspark Fetal-Health-Classification-with-Pyspark Public

   Jupyter Notebook 2

4. Default-prediction-unisng-LR-with-validation-set-approach Default-prediction-unisng-LR-with-validation-set-approach Public

   logistic regression is used to predict the probability of default using income and balance on the Default data set. I also estimated the test error of this logistic regression model using the valid…

   Jupyter Notebook 2

5. SNA-for-a-novel-analysis SNA-for-a-novel-analysis Public

   Book analysis using social network analysis

   R 2

6. Timeseries_Quarterly-Coal-Power-Analysis Timeseries_Quarterly-Coal-Power-Analysis Public

   A comprehensive analysis using AR, MA, ARMA, and ARIMA models for quarterly coal power consumption forecasting. This work delves into data preprocessing, stationarity testing, trend and seasonality…

   Jupyter Notebook 1