Research and Development

Normal Distribution A Detailed Step-by-Step Explanation

Artificial Intelligence, Machine Learning, Machine Learning, Mathematics, Probability and Statistics, Research and Development, Statistics /

Normal Distribution A Detailed Step-by-Step Explanation By Bindeshwar Singh Kushwaha PostNetwork Academy Introduction: Random Variables A random variable (r.v.) is a function that assigns a numerical value to each outcome of a random experiment. There are two main types of random variables: Discrete Random Variable: Takes countable values (e.g., number of heads in 3 coin […]

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Hypergeometric Distribution A Distribution of Dependent Events #175 Data Sc. and A.I. Lect. Series

Artificial Intelligence, Machine Learning, Probability and Statistics, Research and Development /

    Hypergeometric Distribution : A Distribution of Dependent Events By Bindeshwar Singh Kushwaha PostNetwork Academy Introduction In the previous sections, we studied distributions such as the binomial distribution. The binomial distribution assumes that each trial is independent and the probability of success remains constant. However, in many real-life problems, selections are made without replacement.

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What is an Image and How is it Stored on a Computer?

Artificial Intelligence, Image Processing and Computer Vision, Research and Development /

What is an Image and How it is Stored on a Computer Author: Bindeshwar Singh Kushwaha Published by: Postnetwork Academy 📸 Concept of an Image An image can be thought of as a 2D function: $$ f(x, y) $$ Each point \( (x, y) \) in the function maps to an intensity or color value.

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Feature Scaling in Machine Learning : Preprocessing Technique

Artificial Intelligence, Data Handling, Machine Learning, Research and Development /

Feature Scaling in Machine Learning Author: Bindeshwar Singh Kushwaha Postnetwork Academy Why Feature Scaling? Machine learning algorithms often struggle when input features have different scales. Example: Total number of rooms might range from 6 to 39,320, while median incomes range from 0 to 15. Two common methods to scale features: Min-Max Scaling (Normalization) Standardization Min-Max

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Fine-Tuning Large Language Models (LLMs) ( DistilGPT-2)

Artificial Intelligence, Generative A. I., Research and Development /

Transfer Learning and Fine-Tuning Large Language Models In this post, we will explore the concept of Transfer Learning, its connection to fine-tuning large language models (LLMs), and step-by-step instructions to fine-tune DistilGPT-2. What is Transfer Learning? Transfer Learning is a powerful machine learning technique where a model trained on one task is reused as the

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The Regression Revolution: How Sir Francis Galton’s Work Laid the Groundwork for Neural Networks

Research and Development /

  Author: Bindeshwar Singh Kushwaha Institute: PostNetwork Academy Sir Francis Galton: Biography and Contributions Quick Facts Name: Sir Francis Galton, FRS FRAI Born: 16 February 1822, Birmingham, England Died: 17 January 1911, Haslemere, Surrey, England (Aged 88) Resting Place: Claverdon, Warwickshire, England Education: King’s College London, Trinity College Cambridge Father: Samuel Tertius Galton Relatives: Charles

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Research

What is Research? How to Write a Research Paper

Research and Development /

What is Research? How to Write a Research Paper Author: Bindeshwar Singh Kushwaha Institute: PostNetwork Academy Outline What is Research? Benefits of Research Research Paper Sections Research Paper Examples Where to Publish Research Papers What is Peer Review? What is Impact Factor? Where to Start from? What is Research? Systematic investigation to discover new knowledge

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Moments of Binomial Distribution Video I Data Science and A.I. Lect. Series

Artificial Intelligence, Machine Learning, Probability and Statistics, Research and Development, Statistics /

  Moments of Binomial Distribution By Bindeshwar Singh Kushwaha — PostNetwork Academy Moment Definition Let \( X \sim B(n, p) \) be a binomial random variable. The \( r^\text{th} \) raw moment about origin: \( \mu_r’ = \mathbb{E}(X^r) = \sum_{x=0}^{n} x^r \cdot \mathbb{P}(X = x) \) First-order moment (mean): \( \mu_1′ = \mathbb{E}(X) \) Binomial

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But What A Neural Network Learns Actually: Neural Network Architecture for Iris Data Set

Artificial Intelligence, Machine Learning, PyTorch, Research and Development /

 Neural Network Architecture for Iris Dataset Author: Bindeshwar Singh Kushwaha Institution: PosstNetwork Academy  Outline Iris Dataset Overview Neural Network Architecture Mathematical Formulation Code Walkthrough Live Loss Plot Evaluation and Summary  Sample from Iris Dataset Sepal Length Sepal Width Petal Length Petal Width Class 5.1 3.5 1.4 0.2 Setosa 6.2 2.9 4.3 1.3 Versicolor 5.9 3.0

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