As a data science and analytics expert, I have experience building and deploying models that deliver value. I am skilled at turning business problems into actionable insights using a range of tools and techniques. I am passionate about using data science and AI to drive innovation..
This project, part of the Coursera Data Science Coding Challenge, aims to predict loan defaults based on various borrower-specific features. Understanding the patterns and correlations in the data allows lenders to better predict and mitigate potential loan defaults, ensuring a healthier portfolio and risk management.
mlskeleton, the open-source python package, can help you create a professional and organized folder structure for your machine learning projects and streamline your workflow.
Built a project with dbt including modeling, sources, testing, documentation, and deployment
The dashboard is designed to display key insights about user behavior related to booking a ride. It aggregates, cleanses, and combines data from multiple sources to provide a comprehensive analysis. Interactive filters and visualizations are included to help stakeholders gather insights.
Apache Spark is a powerful tool for big data processing, offering both speed and flexibility. However, mastering its debugging and optimization can be challenging. In this blog, we'll explore various aspects of debugging and optimizing Spark applications, providing insights and practical tips.
In this engaging third post of my NLP blog series, I delve into the heart of transformers in Natural Language Processing, focusing on the attention layer—its functions, applications, and advantages. We'll unravel how this layer allows models to weigh the importance of different words in a sentence, providing a nuanced understanding of language context.
Apache Spark is an immensely powerful tool for big data processing, known for its speed, ease of use, and versatility. However, to fully leverage its capabilities, it's crucial to follow certain best practices. In this blog, we’ll explore some key dos and don'ts in Spark, providing a guide to optimize your data processing tasks efficiently.
