This document that I share today, explores the concept of Euclidean distance and its application in measuring user similarity, particularly in the context of recommendation systems. I am sharing clear explanation of Euclidean distance, its calculation, and interpretation of results.
Tag: Data Science
There are 100s of tools available to support Data Scientists to do their day to day job. But due the usefulness, features and ease to use, few are widely popular compared to rest. This document provides a brief overview of
Quantum computing in the Generative AI space is in its early stages, marked by significant research and experimental developments. While practical applications are limited by current technological constraints, ongoing advancements and increasing investment suggest a promising future where quantum computing
Research papers often present a daunting level of complexity or an overwhelming amount of detail that can be challenging to understand and comprehend. Generative AI can make this process of understanding and decoding the document very easy. The document discusses
Data Science and AI are the basis of Credit Risk. Knowing how various models are created for credit risk (All Major Scores details are publicly available), you can leverage the same to identify best practices to maintain high credit score.
Today’s post shares a summary of key performance indicators (KPIs) for validating large language models (LLMs). It offers concise explanations and formulas for each KPI, along with example values to illustrate what constitutes “good” and “poor” model performance. The KPIs
Credit Scoring Central Agencies are different across different nations. In this article I am going to cover some of the key Credit Scores, and the important parameters for them. For USA Credit Agencies, actual distribution of parameters weights is available
In the previous post we have talked about how Data Science is critical element for Credit Risk. With the invent of Generative AI, LLM models, faster GPUs, there are multiple different applications opening up in the area of Credit Risk.
Credit Risk is one of the key area where Data Science is leveraged heavily, and from many decades now. Today I will cover how Data Science plays a key role in Credit Risk, and they areas it is used. The
SQL remains a key element to begin the path of Data Science. In the upcoming posts, I will cover various aspects of SQL. But first, the initial step is to access a server to run queries freely. In this document,