## Probability

1. Fundamentals a. Experiment: An experiment (or trial) is any procedure or action that produces a definite outcome. For instance, rolling a die is an experiment because the result is uncertain…

## “Attention” Is All You Need

Introduced The Transformer, a neural network architecture relying solely on self-attention mechanisms. This innovation quickly became the dominant model for various sequence-to-sequence tasks, such as machine translation, text summarization, and…

## Mastering Descriptive Statistics: From Central Tendency to Box Plots and Beyond

Descriptive statistics refers to the branch of statistics that involves summarizing, organizing, and describing data using various numerical measures and graphical representations. It focuses on analyzing and presenting the characteristics…

## Understanding Probability Distribution Curves: A Mathematical and Programmatic Perspective

Introduction Probability distribution curves are fundamental concepts in statistics, providing insights into the likelihood of different outcomes in a random process. They serve as powerful tools to model and analyze…

## Basic Python data types and structures

Python has several built-in data types and structures that are commonly used in programming and data analysis. Here are some of the most important ones: Numbers: Python has two main…

## Introduction to NumPy

NumPy (short for "Numerical Python") is a Python library that provides support for large, multi-dimensional arrays and matrices, along with a variety of mathematical functions to operate on these arrays.…

NumPy arrays can be used to load, manipulate and analyze data in Python. Here's an overview of how to load and manipulate data with NumPy arrays: Loading data NumPy provides…

## NumPy array operations and Broadcasting

NumPy provides a wide range of operations that can be performed on arrays, including mathematical, logical, and relational operations. These operations can be used to manipulate data in a variety…