InTech Impact Insightsbyashutosh nayak·Mar 17, 2024Tricks of Getting Desired Output from LLMs in RAGs: Purely AnecdotalThere are multiple sources on learning “Prompt Engineering”. This blog is not on “How to prompt” and I assume you already know the basics…
InTech Impact Insightsbyashutosh nayak·Mar 17, 2024Brief Introduction to Different Types of Prompting for LLMsPrompt engineering aims at designing prompts to get the desired output from LLMs. While prompt engineering is vast, this blog briefly…
ashutosh nayak·Aug 19, 2022Decision Tree: What is Information Gain Criteria to Split NodesThis is a short blog on understanding the idea behind splitting a tree at a node (into two sub-branches). One of the criteria is…
InTDS Archivebyashutosh nayak·Sep 1, 2020p-Value and Power of a TestIdea of p-ValueA response icon1A response icon1
InTDS Archivebyashutosh nayak·Dec 22, 2019Idea Behind LIME and SHAPIntuition behind ML interpretation modelsA response icon2A response icon2
InTDS Archivebyashutosh nayak·Dec 17, 2019XGBoost: An Intuitive ExplanationHow XGBoost trees are constructed
InTDS Archivebyashutosh nayak·Jun 22, 2019Cross-entropy: From an Information theory point of viewConnecting Information theory with cross-entropy loss function
InTDS Archivebyashutosh nayak·Jun 2, 2019Dealing with Type II EndogeneityExamples from the literature dealing with Type II endogeneity
InTDS Archivebyashutosh nayak·Jun 2, 2019Dealing with Type I endogeneityUsing ice-cream vendor example to explain Type I endogeneity
