Decision Tree Learning

Decision Tree Learning is a method of approximating discrete-valued target functions, in which the learned function is represented by a decision tree. Coursera's Decision Tree Learning catalogue will guide you in understanding this supervised learning method extensively used in machine learning and data mining. You'll learn how to build, visualize, and optimally prune decision trees for prediction and classification. This catalogue will also teach you about attribute selection measures, overfitting, randomness, and ensemble methods within decision tree learning. In mastering this skill, you'll be equipped to solve complex problems in areas such as finance, healthcare, and natural language processing using decision tree learning algorithms.
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Results for "decision tree learning"

  • Status: Preview

    Fundação Instituto de Administração

    Skills you'll gain: Decision Making, Strategic Decision-Making, Data-Driven Decision-Making, Behavioral Economics, Analysis, Business Risk Management, Complex Problem Solving, Risk Analysis, Systems Thinking, Decision Tree Learning, AI Product Strategy, Virtual Teams, Psychology

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial

    University of Pennsylvania

    Skills you'll gain: Feature Engineering, Unsupervised Learning, Predictive Modeling, Predictive Analytics, Decision Tree Learning, Classification And Regression Tree (CART), Supervised Learning, Forecasting, Random Forest Algorithm, Scikit Learn (Machine Learning Library), Data Analysis, Regression Analysis, Machine Learning, Python Programming

    Beginner · Course · 1 - 4 Weeks

  • Coursera Project Network

    Skills you'll gain: Predictive Modeling, Applied Machine Learning, Scikit Learn (Machine Learning Library), Data Analysis, Data Import/Export, Google Cloud Platform, Jupyter, Decision Tree Learning, Data Processing, Machine Learning, Random Forest Algorithm, Statistical Visualization

    4.7
    Rating, 4.7 out of 5 stars
    15 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial

    University of Washington

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Predictive Analytics, Statistical Modeling, R Programming, Statistical Methods, Decision Tree Learning, Statistical Inference, Statistical Analysis, Machine Learning Algorithms, Machine Learning, Graph Theory, Probability & Statistics, Network Analysis, Big Data, Sampling (Statistics), Random Forest Algorithm

    4.1
    Rating, 4.1 out of 5 stars
    322 reviews

    Mixed · Course · 1 - 4 Weeks