Godwin Paul Vincent

Basic Linear Algebra Subprograms (BLAS), a term I encountered w hile working with the LLAMA (LLM model from Meta) on my windows machine seems to directly affect the performance of the model's inference. Most probably you (like me) already have BLAS capabilities on your windows machine and may be missing on the chance to leverage its capabilities. Lets understand the steps to ensure you are aware of BLAS and its implementation on your machine. Introduction: Basic Linear Algebra Subprograms (BLAS) is the standard that outlines a collection of fundamental routines designed to execute prevalent linear algebra operations, including vector addition, scalar multiplication, dot products, linear combinations, and matrix multiplication. Universally recognized as the standard foundational routines for linear algebra libraries, BLAS routines offer bindings for both C, through the "CBLAS interface," and Fortran, known as the "BLAS interface." While the BLAS specification is

Telecom Churn Case Study Upgrad Telecom Churn Case Study ¶ Overview ¶ In the telecom industry, customers are able to choose from multiple service providers and actively switch from one operator to another. In this highly competitive market, the telecommunications industry experiences an average of 15-25% annual churn rate. Given the fact that it costs 5-10 times more to acquire a new customer than to retain an existing one, customer retention has now become even more important than customer acquisition. For many incumbent operators, retaining high profitable customers is the number one business goal. Business Objective ¶ The objective is to reduce customer churn and improve customer retention in a highly competitive market. Retaining high profitable customers is the number one business goal Case Study Objective ¶ The goal is to build a machine learning model using customer-level data to identify customers at high risk of churn.