Bindeshwar S. Kushwaha

Poisson Distribution | Data Sc. and A.I. Lect. Series

Artificial Intelligence, Data Handling, Machine Learning, Mathematics, Probability and Statistics /

📘 Understand Poisson Distribution 📌 Introduction In binomial distributions, events’ occurrences and non-occurrences are equally important. However, in real-life situations: Events do not occur as outcomes of fixed number of trials. Events occur randomly over time. Interest lies only in the number of occurrences. Examples: Number of printing mistakes per page in a book. Number […]

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Binomial Distribution Mean and Variance Related Problems| Data Sc. and A.I. Lect. Series

Artificial Intelligence, Machine Learning, Probability and Statistics /

Binomial Distribution: Mean and Variance Problem 1: Mean = 3, Variance = 4? Given: Is it possible a binomial distribution has a mean of 3 and a variance of 4? Solution: Mean: \( \mu = np \) Variance: \( \sigma^2 = npq \), where \( q = 1 – p \) Given: \( np =

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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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Fitting Binomial Distribution | Data Science and A.I. Lecture Series

Artificial Intelligence, Data Handling, Probability and Statistics, Statistics /

Fitting Binomial Distribution Introduction Fitting a binomial distribution involves comparing observed frequencies with expected frequencies derived from the binomial probability formula. The recurrence relation simplifies the process of finding probabilities. This technique is useful for testing if a dataset follows a binomial distribution. Binomial Probability Function The binomial probability function is: $$p(x) = {n \choose

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Introduction to Robotics Simulation with PyBullet

Robotics /

Introduction to Robotics Simulation with PyBullet Author: Bindeshwar Singh Kushwaha Institute: PostNetwork Academy What is Robotics? Robotics is an exciting and fast-growing interdisciplinary field that combines mechanical engineering, electrical engineering, computer science, and control systems. Robots are programmable machines capable of performing tasks automatically or semi-automatically, either with minimal human intervention or fully autonomously. The

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Span and Intersection of Subspaces | Linear Algebra Explained

Linear Algebra /

Span and Intersection of Subspaces Author: Bindeshwar Singh Kushwaha Institute: PostNetwork Academy Linear Span: Definition and Properties Given vectors \( u_1, u_2, \ldots, u_m \) in a vector space \( V \), their linear span is the set of all linear combinations: \[ \text{span}(u_1, u_2, \ldots, u_m) = \{ a_1 u_1 + a_2 u_2 +

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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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Moment Generating Function of Binomial Distribution

Artificial Intelligence, Generative A. I., Machine Learning, Probability and Statistics, Statistics /

Moment Generating Function of Binomial Distribution Author: Bindeshwar Singh Kushwaha Institute: PostNetwork Academy Definition of Moment Generating Function The moment generating function (m.g.f.) of a random variable \( X \) is defined as: \[ M_X(t) = E(e^{tX}) \] For a continuous random variable: \[ M_X(t) = \int_{-\infty}^{\infty} e^{tx} f(x) \, dx \] For a discrete

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