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"

  • 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

  • EIT Digital

    Skills you'll gain: Data Mining, Medical Imaging, Image Analysis, Unstructured Data, Health Informatics, Big Data, Health Information Management and Medical Records, Text Mining, Health Care, Analytics, Data Ethics, Natural Language Processing, Medical Science and Research, Predictive Analytics, Innovation, Decision Tree Learning, Artificial Neural Networks

    3.7
    Rating, 3.7 out of 5 stars
    25 reviews

    Beginner · Course · 1 - 3 Months

  • 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

  • Status: Free Trial

    University of California, Irvine

    Skills you'll gain: Predictive Modeling, Predictive Analytics, Classification And Regression Tree (CART), Regression Analysis, Decision Tree Learning, Statistical Modeling, Supervised Learning, Data Analysis, Forecasting, Machine Learning, Unsupervised Learning, Statistical Analysis, Time Series Analysis and Forecasting

    4.5
    Rating, 4.5 out of 5 stars
    73 reviews

    Intermediate · Course · 1 - 4 Weeks

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