Making a trained model (machine learning) from 3D models
jacksparrow Making a Trained Model from 3D Models Creating a Trained Machine Learning Model from 3D Data 1. Data Acquisition and Preparation Gather 3D models: Collect a dataset of 3D models…
September 2024
difference between Tokenization and Segmentation
Tokenization vs. Segmentation Tokenization vs. Segmentation: A Comparative Analysis In the realm of natural language processing (NLP), tokenization and segmentation are fundamental techniques that play a crucial role in preparing…
OCR for Devanagari (Hindi / Marathi / Sanskrit)
OCR for Devanagari (Hindi / Marathi / Sanskrit) Introduction Optical Character Recognition (OCR) plays a crucial role in converting scanned images of text into machine-editable formats. This is particularly relevant…
Benefits of TDD in machine learning
Benefits of TDD in Machine Learning Benefits of TDD in Machine Learning Test-Driven Development (TDD) is a software development process where tests are written before the actual code. While traditionally…
Why is naïve Bayes generative?
Why is Naive Bayes Generative? Understanding Generative Models What is a Generative Model? A generative model learns the underlying probability distribution of the data. It can then generate new data…
Searching an Image Database Using SIFT
Searching an Image Database Using SIFT Searching an Image Database Using SIFT Introduction Scale-Invariant Feature Transform (SIFT) is a powerful algorithm for image feature detection and description, widely used in…
How does Google News automatically categorize articles into Tech/Science/Health/Entertainment/etc?
How Google News Categorizes Articles Behind the Scenes: How Google News Categorizes Articles Google News, the world’s leading news aggregator, efficiently organizes countless articles into distinct categories such as Tech,…
Turning a bunch of numeric attributes into a single score
Turning Numeric Attributes into a Single Score Turning a Bunch of Numeric Attributes into a Single Score Often in data analysis, we deal with datasets containing multiple numeric attributes. For…
Q Learning Algorithm for Tic Tac Toe
Q Learning Algorithm for Tic Tac Toe Q Learning Algorithm for Tic Tac Toe Introduction Q-learning is a reinforcement learning algorithm used to train agents to make optimal decisions in…
Efficient algorithm to group points in clusters by distance between every two points
Efficient Algorithm for Point Clustering Efficient Algorithm for Point Clustering Clustering points based on their pairwise distances is a fundamental problem in data analysis. This article explores an efficient algorithm…