<![CDATA[Stories by ashutosh nayak on Medium]]> https://medium.com/@ashutoshnayakkgp?source=rss-107b80e9d9d4------2 https://cdn-images-1.medium.com/fit/c/150/150/2*2qQn19o-tYpJy42VjuuLgg.jpeg Stories by ashutosh nayak on Medium https://medium.com/@ashutoshnayakkgp?source=rss-107b80e9d9d4------2 Medium Sun, 15 Nov 2026 10:28:37 GMT <![CDATA[Tricks of Getting Desired Output from LLMs in RAGs: Purely Anecdotal]]>

There are multiple sources on learning “Prompt Engineering”. This blog is not on “How to prompt” and I assume you already know the basics…

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]]> https://medium.com/scientya/tricks-of-getting-desired-output-from-llms-in-rags-purely-anecdotal-2db98526faf2?source=rss-107b80e9d9d4------2 https://medium.com/p/2db98526faf2 Sun, 17 Mar 2024 17:04:13 GMT 2025-07-25T15:43:06.361Z <![CDATA[Brief Introduction to Different Types of Prompting for LLMs]]>

Prompt engineering aims at designing prompts to get the desired output from LLMs. While prompt engineering is vast, this blog briefly…

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]]> https://medium.com/scientya/brief-introduction-to-different-types-of-prompting-for-llms-78dc436279ac?source=rss-107b80e9d9d4------2 https://medium.com/p/78dc436279ac Sun, 17 Mar 2024 16:55:29 GMT 2025-07-25T15:43:26.199Z <![CDATA[Decision Tree: What is Information Gain Criteria to Split Nodes]]>

This is a short blog on understanding the idea behind splitting a tree at a node (into two sub-branches). One of the criteria is…

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]]> https://medium.com/@ashutoshnayakkgp/decision-tree-what-is-information-gain-criteria-to-split-nodes-f4f44c202a80?source=rss-107b80e9d9d4------2 https://medium.com/p/f4f44c202a80 Fri, 19 Aug 2022 07:03:40 GMT 2022-08-19T07:03:40.905Z <![CDATA[p-Value and Power of a Test]]>

Idea of p-Value

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]]> https://medium.com/data-science/p-value-and-power-of-a-test-fde61dd8c742?source=rss-107b80e9d9d4------2 https://medium.com/p/fde61dd8c742 Tue, 01 Sep 2020 13:08:40 GMT 2020-09-01T13:08:40.911Z <![CDATA[Akaike Information Criteria]]>

The idea behind AIC

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]]> https://medium.com/data-science/akaike-information-criteria-942d1f554537?source=rss-107b80e9d9d4------2 https://medium.com/p/942d1f554537 Fri, 13 Mar 2020 20:51:25 GMT 2020-03-13T20:51:25.856Z <![CDATA[Idea Behind LIME and SHAP]]>

Intuition behind ML interpretation models

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]]> https://medium.com/data-science/idea-behind-lime-and-shap-b603d35d34eb?source=rss-107b80e9d9d4------2 https://medium.com/p/b603d35d34eb Sun, 22 Dec 2019 14:59:17 GMT 2019-12-22T14:59:17.089Z <![CDATA[XGBoost: An Intuitive Explanation]]>

How XGBoost trees are constructed

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]]> https://medium.com/data-science/xgboost-an-intuitive-explanation-88eb32a48eff?source=rss-107b80e9d9d4------2 https://medium.com/p/88eb32a48eff Tue, 17 Dec 2019 09:22:07 GMT 2019-12-20T22:54:00.496Z <![CDATA[Cross-entropy: From an Information theory point of view]]>

Connecting Information theory with cross-entropy loss function

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]]> https://medium.com/data-science/cross-entropy-from-an-information-theory-point-of-view-456b34fd939d?source=rss-107b80e9d9d4------2 https://medium.com/p/456b34fd939d Sat, 22 Jun 2019 04:58:22 GMT 2019-06-22T04:58:22.380Z <![CDATA[Dealing with Type II Endogeneity]]>

Examples from the literature dealing with Type II endogeneity

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]]> https://medium.com/data-science/endogeneity-the-reason-why-we-should-know-about-data-part-iii-50380e0d996e?source=rss-107b80e9d9d4------2 https://medium.com/p/50380e0d996e Sun, 02 Jun 2019 11:57:41 GMT 2019-06-24T14:28:49.011Z <![CDATA[Dealing with Type I endogeneity]]>

Using ice-cream vendor example to explain Type I endogeneity

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]]> https://medium.com/data-science/endogeneity-the-reason-why-we-should-know-about-data-part-ii-c1487d69aeed?source=rss-107b80e9d9d4------2 https://medium.com/p/c1487d69aeed Sun, 02 Jun 2019 05:34:43 GMT 2019-06-24T14:29:28.800Z