dharmanath patil 🤟🏻 – Medium

dharmanath patil 🤟🏻

dharmanath patil 🤟🏻

Errors in Hypothesis testing

In order to understand this blog you should know what is hypothesis testing and intuition behind it. If you are not familiar with the…

Jan 20, 2023

Errors in Hypothesis testing

Jan 20, 2023

dharmanath patil 🤟🏻

Marginal, conditional and joint distributions

The first distribution most people are made familiar with is the Normal — or Gaussian — distribution. It makes sense, since many processes…

Jun 25, 2022

Marginal, conditional and joint distributions

Jun 25, 2022

dharmanath patil 🤟🏻
in
Analytics Vidhya

Monty Hall Problem — Theoretical Vs Experimental Probabilities

Understanding theoretical and experimental probabilities using the Monty Hall problem

Sep 4, 2019

Monty Hall Problem — Theoretical Vs Experimental Probabilities

Sep 4, 2019

dharmanath patil 🤟🏻

Geometric random variables

In this post, we will understand what are geometric random variables. To understand geometric random variables, it is required to…

Aug 30, 2019

Geometric random variables

Aug 30, 2019

dharmanath patil 🤟🏻
in
Towards Data Science

Divergence in Binomial Random Variable

In this post, we will understand how number of dependent trails or samples influence the binomial variable. Before moving into this topic…

Aug 28, 2019

Divergence in Binomial Random Variable

Aug 28, 2019

dharmanath patil 🤟🏻

Binomial Variable

Definition

Aug 28, 2019

Binomial Variable

Aug 28, 2019

dharmanath patil 🤟🏻
in
Analytics Vidhya

Probability distributions

Constructing probability distribution for random variables

Aug 27, 2019

Probability distributions

Aug 27, 2019

dharmanath patil 🤟🏻

Types Of Random Variables

Discrete & Continuous —the mighty brothers

Aug 26, 2019

Types Of Random Variables

Aug 26, 2019

dharmanath patil 🤟🏻

Random Variables

Understanding random variables

Aug 26, 2019

Random Variables

Aug 26, 2019

dharmanath patil 🤟🏻

dharmanath patil 🤟🏻

I’m a Sr. Data Scientist at Youplus Inc. and this is my notepad for Applied Math / CS / Deep Learning / NLP topics.

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