Bindeshwar S. Kushwaha

Bivariate Continuous Random Variables

  Bivariate Continuous Random Variables Introduction A bivariate continuous random variable extends the concept of a single continuous random variable to two dimensions. It describes situations where two variables vary continuously and have some form of dependence or interaction. Understanding these concepts is fundamental in probability theory, statistics, and data science. Objectives Define bivariate continuous

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IBM Research and Hugging Face Introduce SmolDocling: A Compact Vision-Language Model for Document Conversion

IBM Research and Hugging Face Introduce SmolDocling: A Compact Vision-Language Model for Document Conversion IBM Research and Hugging Face have unveiled SmolDocling, an ultra-compact vision-language model designed for end-to-end document conversion. Unlike traditional models that rely on large foundational architectures or complex pipelines, SmolDocling offers a lightweight, efficient solution for processing entire documents while preserving

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Bivariate Discrete Cumulative Distribution Function

Bivariate Discrete Cumulative Distribution Function Data Science and A.I. Lecture Series Author: Bindeshwar Singh Kushwaha Institute: PostNetwork Academy Joint and Marginal Distribution Functions for Discrete Random Variables Two-Dimensional Joint Distribution Function The distribution function of the two-dimensional random variable \((X, Y)\) for all real \(x\) and \(y\) is defined as: \[ F(x,y) = P(X \leq

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Bivariate Discrete Random Variables Data Science and A.I. Lecture Series

Bivariate Discrete Random Variables Data Science and A.I. Lecture Series By Bindeshwar Singh Kushwaha, PostNetwork Academy Definition Let \( X \) and \( Y \) be two discrete random variables defined on the sample space \( S \) of a random experiment. Then, the function \( (X, Y) \) defined on the same sample space

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Continuous Cumulative Distribution Function (CDF) | Probability & Statistics

  Definition: Continuous CDF A continuous random variable can take an infinite number of values in a given range. The Probability Density Function (PDF) \( f(x) \) describes the likelihood of \( X \) falling within a small interval. The Cumulative Distribution Function (CDF) is given by: \[ F(x) = P[X \leq x] = \int_{-\infty}^{x}

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Ordinary Least Squares (OLS) Regression: Step-by-Step Guide with Derivation & Visualization

Ordinary Least Squares (OLS) Regression Author: Bindeshwar Singh Kushwaha Institute: PostNetwork Academy Dataset of a Company X (Budget) Y (Sales) 1 2 2 2.8 3 3.6 4 4.5 5 5.1 Description: The dataset represents the relationship between advertising budget (\(X\)) and sales revenue (\(Y\)). The company wants to analyze how the budget affects sales using

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Differential Equations

Definition of Differential Equations A differential equation is an equation that involves one or more derivatives of an unknown function. Example: \[ \frac{dy}{dx} = 3x^2 \] Types of Differential Equations Ordinary Differential Equations (ODEs): \( \frac{dy}{dx} + 2y = x^2 \) Partial Differential Equations (PDEs): \( \frac{\partial u}{\partial x} + \frac{\partial u}{\partial y} = 0

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Tokens in Python

  Tokens in Python Introduction Tokens are the smallest individual units in a Python program. Everything in a Python program is built using tokens. Python has five types of tokens: Keywords: Reserved words in Python. Identifiers: Names given to variables, functions, and classes. Literals: Fixed values such as numbers, strings, and boolean values. Operators: Symbols

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