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AI initials models

How Models Work

  • Real estate example
  • Decision tree
  • Deeper trees

Models to explore:

  • Linear regression: A statistical technique that is used to model the relationship between a dependent variable and one or more independent variables.

  • Logistic regression: A statistical technique that is used to model the relationship between a dependent variable and one or more independent variables in binary classification problems.

  • Decision trees: A simple yet powerful machine learning algorithm that is used for both classification and regression tasks.

  • Naive Bayes: A probabilistic machine learning algorithm that is based on Bayes' theorem, used for classification tasks.

  • K-means clustering: An unsupervised machine learning algorithm that is used to partition a dataset into K clusters based on their similarities.

  • Random Forest: A popular ensemble learning method that combines multiple decision trees to improve the accuracy of the model.

  • Support Vector Machines (SVMs): A popular supervised learning algorithm that is used for classification and regression tasks.

  • Artificial Neural Networks (ANNs): A family of machine learning models inspired by the structure and function of biological neural networks, used for a variety of tasks such as image recognition, natural language processing, and speech recognition.