Bindeshwar S. Kushwaha

Tensors in Pytorch

Understanding PyTorch: Tensors, Vectors, and Matrices

PyTorch /

Understanding PyTorch: Tensors, Vectors, and Matrices By: Bindeshwar Singh Kushwaha Institute: PostNetwork Academy What is PyTorch? PyTorch is an open-source deep learning framework. It supports dynamic computation graphs. Designed to be Pythonic and flexible. Commonly used for research and production in AI/ML. Types of Tensors A scalar is a 0-dimensional tensor. A vector is a […]

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Building a Smart Indian Food Recommender Using TinyLlama, Ollama, and Python

Artificial Intelligence, Data Handling, Deep Learning, Generative A. I., IoT, Machine Learning /

Building a Smart Indian Food Recommender Using TinyLlama, Ollama, and Python In this tutorial, we’ll build a simple yet smart food recommender system that suggests Indian dishes based on the current humidity and temperature values. The system uses a local language model TinyLlama running via Ollama, and Python’s random.randint() function to simulate real-time weather. Why

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Binomial Distribution Data Science and A.I. Lecture Series

Artificial Intelligence, Data Handling, Generative A. I., Mathematics, Maths, Probability and Statistics, Research and Development, Statistics /

  Binomial Distribution Data Science and A.I. Lecture Series By Bindeshwar Singh Kushwaha | PostNetwork Academy Binomial Probability Function The binomial probability function is given by: \[ P(X = k) = \binom{n}{k} p^k (1 – p)^{n – k} \] where: \( n \) = total number of trials \( k \) = number of successes

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Bernoulli Distribution in Probability and Statistics

Artificial Intelligence, Data Handling, Machine Learning, Mathematics, Maths, Research and Development, Statistics /

Bernoulli Distribution Data Science and A.I. Lecture Series By Bindeshwar Singh Kushwaha | PostNetwork Academy Introduction to Bernoulli Distribution A Bernoulli trial is an experiment with only two possible outcomes: Success (1) and Failure (0). If p is the probability of success, then q = 1 – p is the probability of failure. A random

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Addition, Multiplication Theorem of Expectation and Covariance

Artificial Intelligence, Calculus, Mathematics, Maths, Probability and Statistics, Programming, Python, Research and Development, Statistics /

Addition, Multiplication Theorem of Expectation and Covariance Data Science and A.I. Lecture Series By Bindeshwar Singh Kushwaha PostNetwork Academy Outline Introduction Addition Theorem of Expectation Proof of Addition Theorem Multiplication Theorem of Expectation Proof of Multiplication Theorem Covariance Introduction Expectation (or expected value) is a fundamental concept in probability and statistics. It provides a measure

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Moments and Other Measures in Terms of Expectations

Artificial Intelligence, Data Handling, Machine Learning, Mathematics, Maths, Research and Development, Statistics /

  Moments and Other Measures in Terms of Expectations Data Science and A.I. Lecture Series By Bindeshwar Singh Kushwaha – PostNetwork Academy Moments The \( r^{th} \) order moment about any point \( A \) of a variable \( X \) is given by: For discrete variables: \[ \mu_r’ = \sum_{i=1}^{n} p_i (x_i – A)^r

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Mathematical Expectation

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

Mathematical Expectation Data Science and A.I. Lecture Series By Bindeshwar Singh Kushwaha – PostNetwork Academy Introduction This unit explores the expectation of a random variable. Expectation provides a measure of central tendency in probability distributions. Expectation is useful in both discrete and continuous probability distributions. Problems and examples help in understanding practical applications. Objectives Define

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Operators in Python Programming

Artificial Intelligence, Machine Learning, Programming, Python /

  Operators in Python Data Science and A.I. Lecture Series Author: Bindeshwar Singh Kushwaha | Institute: PostNetwork Academy Introduction Operators in Python are special symbols that perform computations on operands. Python provides various types of operators: Arithmetic Operators Relational Operators Logical Operators Bitwise Operators Assignment Operators Membership Operators Identity Operators Arithmetic Operators a = 10

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Understanding Input and Output in Python

Machine Learning, Programming, Python /

  Python Input and Output Understanding Input and Output in Python Author: Bindeshwar Singh Kushwaha | Institute: PostNetwork Academy What is Input and Output? In Python, input and output refer to the mechanisms by which a program interacts with users. Input: Data provided by the user using the input() function. Output: Information displayed using the

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