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Machine learning (ML) is a branch of artificial intelligence (AI) that enables computers to learn from data and improve their performance without being explicitly programmed. Instead of following a set of hardcoded instructions, machine learning models use algorithms to identify patterns, make decisions, and perform tasks autonomously. Here's a detailed overview: Types of Machine Learning Supervised Learning: Involves training a model on labeled data, where the input-output pairs are known. The model learns to predict the output for new, unseen inputs. Common Algorithms: Linear Regression Logistic Regression Support Vector Machines (SVM) Decision Trees Neural Networks Example: Predicting house prices based on features like size, location, etc. Unsupervised Learning: Involves training a model on data that is not labeled. The goal is to identify underlying patterns or groupings in the data. Common Algorithms: K-means Clustering Hierarchical Clustering Principal Component Analysis (PCA) Autoencoders Example: Customer segmentation based on purchasing behavior. Reinforcement Learning: The model learns by interacting with an environment and receiving feedback in the form of rewards or penalties. The model aims to maximize the cumulative reward over time. Common Algorithms: Q-learning Deep Q Networks (DQN) Policy Gradients Example: Training an AI agent to play video games or robots to navigate environments. Semi-Supervised Learning: Combines labeled and unlabeled data. The model is trained on the small amount of labeled data and the large amount of unlabeled data. Example: Using a few labeled images to help classify a large set of unlabeled images. Key Components of Machine Learning Dataset: Collection of data points used for training and testing models. Typically divided into: Training Set: Used to train the model. Validation Set: Used to tune hyperparameters. Test Set: Used to evaluate the model’s performance on unseen data. [Machine Learning Course in Pune](<>)<https://www.sevenmentor.com/machine-learning-course-in-pune.php>

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