What is Selection Bias and How Does It Affect Data Analysis? In data analysis and machine learning, one of the most significant challenges is ensuring that the data used for training models is representative of the population or real-world scenarios the model will encounter in the future. If the data is skewed, incomplete, or unrepresentative,…
What is a Statistical Interaction? In research and statistical modeling, understanding how independent variables affect a dependent variable is key to drawing meaningful conclusions. However, the effect of one independent variable on the dependent variable can be more complex when other independent variables are involved. This complexity is referred to as statistical interaction. A statistical…
Understanding the Assumptions of Linear Regression Linear regression is a powerful statistical technique used for modeling the relationship between a dependent variable and one or more independent variables. While the model can be highly effective for making predictions, its validity and accuracy depend on certain assumptions being met. These assumptions ensure that the model fits…
What is Linear Regression? Linear regression is one of the simplest and most widely used statistical methods in predictive modeling. It is a technique used to understand the relationship between a dependent variable (also called the target or output) and one or more independent variables (also known as predictors or features). The goal is to…
What are Type I and Type II Errors? In statistical hypothesis testing, researchers use tests to make inferences about a population based on sample data. However, as with any process of decision-making, mistakes can occur. Two common types of errors in hypothesis testing are Type I and Type II errors. Understanding these errors is crucial…
What is SciPy? SciPy is an interactive Python session used as a data-processing library that is made to compete with its rivalries such as MATLAB, Octave, R-Lab, etc. It has many user-friendly, efficient, and easy-to-use functions that help to solve problems like numerical integration, interpolation, optimization, linear algebra, and statistics. The benefit of using the…
In probability theory, a probability distribution is a mathematical function that provides the probabilities of occurrence of different possible outcomes in an experiment. These distributions are either discrete or continuous, depending on whether the outcomes are countable or measurable over a range of values.
Let’s break down AI, Machine Learning (ML), and Neural Networks in a structured way, covering key concepts, types of ML, and model architectures like Transformers, and their applications.
Machine Learning
is a vast and intricate field that requires an understanding of key concepts from mathematics, statistics, programming, and data science. Let’s go through everything step-by-step, from the fundamental maths to the essential skills required to build ML models.
