Machine Learning (ML) includes supervised learning (using labeled data), unsupervised learning (finding patterns in unlabeled data), and reinforcement learning (training models via trial and error for decision-making)..
Machine Learning (ML) enables computers to learn from data, identify patterns, and make predictions without explicit programming. It's essential in AI-driven applications like recommendation systems and fraud detection..
Discover the basics of mean, median, and mode—essential statistics in machine learning. Learn their definitions, differences, and applications to understand and preprocess data, enhancing the performance of machine learning models.
