Design Sprint
Confused after leaving the subway? New concept feature that improves urban navigation designed in just 5 days!
Imagine you have been underground for a while. You come out of the public transit to find yourself surrounded by unfamiliar buildings, a densely packed crowd walking in all directions speaking in a foreign language, and cars honking. You feel like you are standing out and decide to take a left. After walking for a few minutes, you realize you are going in the opposite direction.
As someone with no sense of directions, moving to and getting around in Brazil and Germany as an international student wouldn’t have been possible without Google Maps. However, navigating in big cities like São…
NLP in Finance
Tutorial on how to build a production-ready Financial QA system
Part 1 — Learn how to use the neural search framework, Jina, to build a Financial Question Answering (QA) search application with the FiQA dataset, PyTorch, and Hugging Face transformers.
Part 2 — Learn how evaluate and improve your Financial QA search results with Jina
For my master’s thesis, I built a Financial QA system using a fine-tuned BERT model called FinBERT-QA. Motivated by the emerging demand in the financial industry for the automatic analysis of unstructured and structured data at scale, QA systems can provide lucrative and competitive advantages to companies by facilitating the decision making of financial advisers.
Geospatial Analytics
Vision: Using data to enable marketers to determine where to place their advertisements
Client: Intermx
Team: 1 Designer (Me), 1 Product Design Lead
My Role: Ideation, UI Design, Prototyping
Duration: 2 days
Tool: Figma
Overview
Problem: An advertising company wants to find out how people of Columbus, Ohio have been moving around from January 2019 to January 2021 across its neighborhoods.
Understanding the data behind how people move and the demographics of these people can provide actionable insights to advertising companies. …
NLP in Finance
Tutorial on how evaluate and improve your Financial QA search results with Jina
Part 1 — Learn how to use the neural search framework, Jina, to build a Financial Question Answering (QA) search application with the FiQA dataset, PyTorch, and Hugging Face transformers.
Part 2 — Learn how evaluate and improve your Financial QA search results with Jina
In the previous tutorial we learned how to build a production-ready Financial Question Answering search application with Jina and BERT. In order to improve our application and retrieve meaningful answers, evaluating the search results is essential for tuning the parameters of the system. …
