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stratified-sampling

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Data consists of tweets scrapped using Twitter API. Objective is sentiment labelling using a lexicon approach, performing text pre-processing (such as language detection, tokenisation, normalisation, vectorisation), building pipelines for text classification models for sentiment analysis, followed by explainability of the final classifier

  • Updated Apr 3, 2022
  • Jupyter Notebook

The objective is to analyze flight delays in the United States. Data from airlines, airports, and runways will be collected and processed. Machine learning models will be built using logistic regression, decision trees, and XGB classifiers. Visualizations will be created in Tableau, and Excel dashboards and SQL queries will be used for analysis.

  • Updated Jun 21, 2023
  • Jupyter Notebook

Three business analytics case studies were undertaken, encompassing market basket analysis, customer segmentation, and campaign management. SAS Visual Data Mining and Machine Learning on SAS Viya was utilized to explore data and provide insights. A comprehensive report addressing both technical and business aspects was delivered.

  • Updated Apr 15, 2024

This project focuses on applying advanced simulation methods for derivatives pricing. It includes Monte-Carlo, Variance Reduction Techniques, Distribution Sampling Methods, Euler Schemes, and Milstein Schemes.

  • Updated Jul 9, 2024
  • Jupyter Notebook

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