Introduction to Data Mining and Machine Learning

EasyChair Preprint no. 13110

Abstract

: Data mining and machine learning represent two interconnected pillars reshaping industries by extracting invaluable insights from vast datasets. Data mining, comprising preprocessing, pattern discovery, and knowledge representation, lays the foundation for uncovering meaningful information. Techniques such as classification, clustering, association rule mining, and anomaly detection empower informed decision-making across diverse domains. Meanwhile, machine learning, the evolution of data mining, leverages algorithms to learn from data, facilitating predictions and decisions autonomously. Supervised, unsupervised, and reinforcement learning paradigms yield a plethora of algorithms, including decision trees, support vector machines, neural networks, and ensemble methods, driving breakthroughs in areas like image recognition and recommendation systems. The symbiotic relationship between data mining and machine learning is integral to their transformative impact. Data mining serves as the precursor, extracting relevant features and patterns from data, which are then utilized by machine learning algorithms to make predictions and decisions autonomously. Real-world applications abound, from healthcare predicting disease outcomes to finance detecting fraud and e-commerce personalizing recommendations. However, challenges such as data quality, scalability, and interpretability persist, alongside ethical considerations regarding privacy and algorithmic bias. Looking ahead, emerging trends like deep learning and explainable AI offer promising solutions to address existing challenges. By integrating data mining and machine learning, society can harness the power of data for informed decision-making and innovation, paving the way for a more data-driven future.

Keyphrases: machine learning, supervised learning, unsupervised learning

@Booklet{EasyChair:13110,
  author = {Harshita Kailash and Harshit Ruhal},
  title = {Introduction to Data Mining and Machine Learning},
  howpublished = {EasyChair Preprint no. 13110},

  year = {EasyChair, 2024}}