Answer / Amit Kumar Rai

Machine Learning techniques are algorithms used by artificial intelligence (AI) to learn and make decisions based on data. These techniques can be broadly classified into three categories: Supervised Learning, Unsupervised Learning, and Reinforcement Learning. In Supervised Learning, the model is trained on labeled data with input-output pairs to predict outputs for new inputs. Examples include Linear Regression, Logistic Regression, Support Vector Machines (SVM), Decision Trees, Random Forests, and Neural Networks. Unsupervised Learning involves finding hidden patterns in unlabeled data without any specific output to predict. Examples include K-Means Clustering, Hierarchical Clustering, Principal Component Analysis (PCA), and Autoencoders. Reinforcement Learning is a method where an agent learns to make decisions by interacting with its environment to maximize some type of reward.

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