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Decision Trees

Decision Trees

Decision Trees are a type of machine learning algorithm that uses a tree-like structure to classify data or make predictions. They are a popular algorithm for classification and regression tasks, and are known for their simplicity and interpretability. What is a Decision Tree? A Decision Tree is a tree-like structure

Linear Regression

Linear Regression

Linear Regression is a type of machine learning algorithm that predicts a continuous output variable based on one or more input features. It's a supervised learning algorithm that learns from labeled data, where each example is a pair of input and output values. What is Linear Regression? Linear

Reinforcement Learning

Reinforcement Learning

Reinforcement Learning is a type of machine learning that involves training an agent to make decisions by interacting with an environment and receiving rewards or penalties for its actions. The goal of Reinforcement Learning is to learn a policy that maximizes a reward function, which is a measure of the

Natural Language Processing

Natural Language Processing

Natural Language Processing Natural Language Processing (NLP) is a subfield of artificial intelligence that deals with the interaction between computers and humans in natural language. It's a powerful tool for analyzing and understanding human language, and has applications in a wide range of fields, including text analysis, speech

Deep Learning

Deep Learning

Deep learning is a type of machine learning that uses artificial neural networks to learn from data and make predictions or decisions. It's a powerful tool for analyzing and understanding complex data, such as images, speech, and text. What is Deep Learning? Deep learning is a type of

Unsupervised Learning

Unsupervised Learning

Unsupervised learning is a type of machine learning where the algorithm is trained on unlabeled data to identify patterns, relationships, and structure in the data. The goal of unsupervised learning is to discover hidden insights and meaning in the data without any prior knowledge of the expected output. Key Characteristics

Supervised Learning

Supervised Learning

Supervised learning is a type of machine learning where the algorithm is trained on labeled data to learn the relationship between the input and output. The goal of supervised learning is to predict the output for new, unseen data. Key Characteristics * Labeled Data: Supervised learning requires labeled data, where each