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Introduction to Bayes Theorem The Naive Bayes algorithm is a simple, probabilistic machine learning method used for classification tasks. It’s based on Bayes’ Theorem, which calculates the probability of an event given prior knowledge. The “naive” part comes from its Read More …
Histogram of Oriented Gradients (HOG) is a feature detection algorithm based on the image’s gradients. It is a classic approach for object detection in an image, e.g., a vehicle in the street, a pedestrian walking in the street, etc. Examples Read More …
Support Vector Machine (SVM) is a supervised machine learning (ML) technique that is used for the classification as well as for regression. It works by finding the optimal hyperplane that best separates data points of different classes with the maximum Read More …
The Frequent Pattern Growth (FP-Growth) algorithm is a highly efficient and popular algorithm for mining frequent itemsets from large transaction databases. It was proposed by Han, Pei, and Yin in 2000 as an improvement over the Apriori algorithm, primarily by Read More …
The Apriori Algorithm is a classic algorithm used in association rule mining and frequent itemset mining over transactional databases. It is particularly useful in market basket analysis, where the goal is to find relationships between items bought together. Key Concepts Read More …
Introduction to Machine Learning Machine learning must be one of the fastest growing fields in computer science. It is not only that the data is continuously getting “bigger,” but also the theory to process it and turn it into knowledge. Read More …
Introduction In linear algebra, matrices are rectangular arrays of numbers, and operations like addition, subtraction, and multiplication follow specific rules. Below, I’ll explain each operation clearly and concisely, assuming you’re familiar with basic matrix notation. Matrix Addition Definition: Two matrices Read More …
Airbag Deployment System in Modern Vehicles Airbag systems are critical safety components in modern vehicles. They are designed to deploy airbags within milliseconds of a collision to protect passengers. This precise, fast response is enabled by digital logic circuits. Digital Read More …
Introduction to Principal Component Analysis In this article, you will learn about in depth about the Principal Component Analysis (PCA) technique which is used for reducing the dimension of data while preserving the variance. It is actually the transformation of Read More …
Introduction to eigen values and eigen vectors How to Find the Eigen Values and Eigen Vectors? explain with examples Eigen Values and Eigen Vectors has a great significance in many engineering problems specially in case of linear systems where we Read More …