Hello, I’m Navya Bhat.
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Data Science and Analytics | Business Intelligence | Machine Learning Engineer | Data Engineer
Contact Navya
Data Science and Analytics | Business Intelligence | Machine Learning Engineer | Data Engineer
Contact Navya
Hello! I'm Navya Bhat, a data explorer driven by a vision to contribute profoundly to forward-thinking organizations. My expertise lies at the intersection of technology and data-driven solutions, aimed at propelling growth, fostering innovation, and ensuring customer success. I am proficient in using data analysis tools like Tableau, Excel and a suite of Python libraries. I am also proficient in programming languages such as R, Python, SQL, pySpark and Java. I am currently delving into the world of Deep Learning, using PyTorch. I thrive on leveraging these tools and Machine Learning to unlock insights and drive strategic decisions.
About MeClassification of loan default risks using ML models like Logistic Regression, GLM, GBM, XGBoost and Light GBM, achieving a robust 93% accuracy through meticulous regularization techniques. Employed cross-validation methods and Optuna for fine-tuning and continuously monitored model performance using diverse metrics. Leveraged SHAP for model explanability, providing invaluable insights into model behavior.
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Utilized Decision Tree algorithms and clustering methods in an Airbnb pricing project, employing sophisticated visualization, feature engineering, and encoding techniques. Seamlessly integrated diverse data visualization strategies to explore patterns and insights, enhancing model understanding and accuracy.
View CodeIn-depth analysis of market share and sales data of Conagra's tablespreads brands using predictive models. Designed new KPIs and deciphered the interactions between various product attributes using SAS, Excel and Tableau.
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Leveraging PyTorch, PyTorch Lightning, and the powerful GPT-2 transformer, crafted a chatbot that delighted users with personalized recipe guidance for their cravings.
View CodeUtilized Fastai's vision library and EfficientNet-B0 model to train a deep-learning model accurately classifies plant diseases from images in a provided dataset resized to a maximum of 600 pixels while maintaining aspect ratios. Achieved an impressive F1 score of 0.864 by fine-tuning the pre-trained model and adapting the classifier for the dataset's classes.
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About 3 years of experience working in a Financial ecosystem at Temenos.I also designed Restful APIs to serve the data to the front-end applications. My role involved architecting Restful APIs tailored to seamlessly serve crucial data to front-end applications. This design not only facilitated efficient data transfer and application experience but also empowered user interfaces with real-time, mission-critical information, fostering agile and data driven strategies. I also delved into the analytics of IoT devices through an internship. This immersive experience broadened my expertise, allowing me to extract valuable insights from complex IoT data streams, enabling informed decision-making based on real-time device analytics.
Linkedin My Resume
Recognition for exceptional mentorship, emphasizing dedication and guidance to uplift fellow graduate students.
Recognition awarded upon completion of Master's degree for exceptional academic achievement and distinction
Award acknowledging demonstrated tenacity and dedication, epitomizing the commitment to go above and beyond.