Case Study: Using DBSCAN algorithm for Clustering and Anomaly Detection on Various Datasets
Introduction In the realm of unsupervised machine learning, clustering algorithms play a pivotal role in identifying patterns, grouping similar data points, and detecting anomalies within datasets. Among these algorithms, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) stands out for its ability to discover clusters of arbitrary shapes and effectively identify outliers without requiring a […]
General vs. Modular Programming Approaches for Machine Learning Projects
Machine learning projects can be structured in various ways, with general programming and modular programming being two common approaches. In this blog post, I’ll compare these methodologies and provide a comprehensive guide to building an ML project using a modular architecture. The Machine Learning Lifecycle Before diving into programming approaches, let’s understand the typical machine […]
Statistics for Machine Learning (Required statistics for Machine learning)
The basic and most important part of the Machine learning and Data analysis is to understand the Data, Analyze the pattern in technical way we will say distribution of the data, we will discuss as follow: To understand the machine learning and data science perfectly you must know the statistics. we are going to discuss […]
Case-study of Machine Learning Hyperparameter Tuning to check Exponential change in Classification and Regression models accuracy
Introduction Hyperparameter tuning plays a crucial role in optimizing the performance of machine learning models. In this case study, we explore the impact of hyperparameter tuning on model accuracy using various supervised learning algorithms for classification and regression tasks. The dataset used in this study is the Holiday Package Prediction Dataset, where the goal is […]