- 😊 Pronouns: She/Her
- 😊 I’m looking for help with projects, job opportunities.
- 💼 Job interests: Data Analysis,Data Scientist,Machine Learning Engineer.
Data Visualization Softwares and Libraries: Microsoft Excel,Microsoft Power Bi,Tableau ,Plotly,Python Visualization Libraries(matplotlib,seaborne,plotly)
Programming Languages: Python
Querying Language: SQL
Frameworks:flask, Tensorflow, Keras, Pytorch, Matplotlib, Seaborn
Developer Tools: Git, Docker, Google Cloud Platform, VS Code, Jupyter Lab,Jupyter Notebook
Libraries: Scikit-Learn, NLTK, NumPy, Pandas, Gensim, Matplotlib, Seaborn, Hugging Face
| ☀️ Projects | 💬 Description of the projects |
| Text-Classification | Text-Classification-with-Transformers-RoBERTa-and-XLNet-Model. |
| Machine learning pipeline with Jenkins | Build-CICD-Pipeline-for-Machine-Learning-Projects-using-Jenkins |
| Image Classification | Image-Classification-using-CNN-Model-with-PyTorch . |
| Speech Emotion | End-to-End-Speech-Emotion-Recognition-Project-using-ANN . |
| Medical Image Segmentation | Medical Image Segmentation. |
| Build-an-AI-Chatbot-from-Scratch-using-Keras-Sequential-Model | Build-an-AI-Chatbot-from-Scratch-using-Keras-Sequential-Model. |
| Loan-Default-Prediction-Project-using-Explainable-AI-ML-Models | This project aims to predict loan defaults using machine learning models (XGBoost and Random Forest) and then enhance model interpretability using Explainable AI techniques for various stakeholders involved in the loan lending process. The project seeks to clearly understand why the models make certain predictions. |
| End-to-End-ML-Model-Monitoring-using-Airflow-and-Docker | End-to-End-ML-Model-Monitoring-using-Airflow-and-Docker. |
| Time-Series-Forecasting-Project-Building-ARIMA-Model-in-Python | Time-Series-Forecasting-Project-Building-ARIMA-Model-in-Python. |
| NLP-Project-for-Multi-Class-Text-Classification-using-BERT-Model | NLP-Project-for-Multi-Class-Text-Classification-using-BERT-Model |
| Machine Learning project for Retail Price Optimization | Machine Learning project for Retail Price Optimization |
| Chatbot with RASA NLU Model and Python | NLP-Project-for-Multi-Class-Text-Classification-using-BERT-Model |
| Customer Churn Prediction | Churned Customers are those who have decided to end their relationship with their existing company.XYZ is a service-providing company that provides customers with a one-year subscription plan for their product. The company wants to know if the customers will renew the subscription for the coming year or not.In this project, Decision tree classifier and ensemble model was used for the predictive analysis. |