Unit 1 MACHINE LEARNING BASIC, Lecture notes of Advanced Data Analysis

Machine Learning (ML) – A branch of AI that enables computers to learn from data and make predictions. Data Science – The process of collecting, analyzing, and interpreting data to gain insights. Artificial Intelligence (AI) – Technology that allows machines to simulate human intelligence. Types of Machine Learning – Supervised, Unsupervised, and Reinforcement Learning. Supervised Learning – ML method where models learn using labeled data. Unsupervised Learning – ML method where models find patterns in unlabeled data. Reinforcement Learning – Learning method based on rewards and punishments. Training Data – Data used to train a machine learning model. Testing Data – Data used to evaluate model performance. Features – Input variables used for prediction in ML models. Applications of ML – Used in healthcare, finance, recommendation systems, and image recognition.

Typology: Lecture notes

2025/2026

Available from 05/22/2026

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