Srishti SawlaMLOps: The Need of the Hour for Every Data ScientistBuilding a powerful ML model is only part of the equation. The real challenge lies in efficiently deploying, monitoring, and maintaining…Sep 9Sep 9
Srishti SawlaThe Power of T-Shaped Skills in Data ScienceIn today’s rapidly evolving data science landscape, standing out and excelling requires more than just technical expertise or domain…Sep 4Sep 4
Srishti SawlaRole of Data Sampling in Supervised Machine LearningIn the vast world of machine learning, data is the lifeblood that fuels the development and deployment of models. Just as the quality of…Sep 3Sep 3
Srishti SawlaSmart Strategies for Handling Missing Data in Machine LearningLet’s explore why these seemingly harmless techniques can turn into expensive mistakes in your data science pipeline.Sep 2Sep 2
Srishti SawlaLearn Basic SQL for Data Science in 10 mins!Learning SQL for data science as a beginner can be broken down into five actionable stepsAug 29Aug 29
Srishti SawlaAre You Defining the Problem Right in Data Science?In data science, where algorithms and models often take center stage, it’s easy to overlook the foundation on which successful projects are…Aug 28Aug 28
Srishti SawlaEmbedded Methods for Feature Selection in Machine LearningFeature selection is a critical step in the machine learning pipeline, helping to enhance model performance, reduce overfitting, and…Aug 26Aug 26
Srishti SawlaWrapper Methods for Feature Selection in Machine LearningIn my previous post, we explored filter methods for feature selection, a simple and efficient approach to identify relevant features based…Aug 24Aug 24
Srishti SawlaIs your data NOT fair?In the world of data science and machine learning, data is the bedrock upon which models are built. However, the data we rely on isn’t…Aug 23Aug 23