Python 

NumPy, Pandas, Matplotlib, Seaborn, scikit-learn, TensorFlow, Keras, PyTorch, OpenCV, BeautifulSoup, Transformers, NLTK, OpenAI, statsmodels, FastAPI

R

tidyverse, dplyr, ggplot2, shiny, flexdashboard, caret 

SQL

Queries, Data Modification, Views, Procedures, Jobs 

Hadoop | Apache Spark

Apache Kafka

Apache Airflow

NoSQL databases (MongoDB, Neo4j, Pinecone)

MLFlow | Weights and Biases

Docker | Kubernetes

Azure | AWS

Git | GitHub | GitHub Actions

Shell | Bash

Power BI

Tableau

Qlik Sense

Oracle BI

Looker Studio

Alteryx

AMPL

@Risk | Crystal Ball

R

Matlab 

Stata

SPSS

Minitab

Figma

LaTeX

VBA

MS Office

Developed an application for generating a question bank by fine-tuning Hugging Face’s LLM models, deployed it in a production environment using containerization and Google Cloud Services, and created a front-end.

Conducted research in Natural Language Processing to investigate the impact of pre-training models with code and mathematical reasoning on entity tracking capabilities.

Leveraging computer vision and transfer learning, this study automates the detection of malaria parasites in microscopic blood sample images. The objective is to enhance early and accurate diagnosis of the disease, offering potential benefits in healthcare.

This study utilizes speed dating data to predict dating interest using various machine learning classification algorithms. Valuable insights for individuals seeking romantic partners are provided based on the analysis. 

This project critically analyzes the beauty standards embedded within the CelebA dataset used for facial recognition in ML. It explores the societal, cultural, and ethical implications of these standards, shedding light on biases and subjectivity in the field.

This project analyzes the 2016 National Study of the Changing Workforce survey to identify factors for workplace satisfaction and happiness. Insights will address talent challenges at policy and organizational levels.