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  • Random Forest Algorithm

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Results for "random forest algorithm"


  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Inferential Statistical Analysis with Python

    Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Statistical Inference, Bayesian Statistics, Probability & Statistics, Statistical Analysis, Sampling (Statistics), Jupyter, Python Programming, Matplotlib, NumPy

    4.6
    Rating, 4.6 out of 5 stars
    ·
    934 reviews

    Intermediate · Course · 1 - 4 Weeks

  • E

    Edge Impulse

    Introduction to Embedded Machine Learning

    Skills you'll gain: Model Evaluation, Applied Machine Learning, Embedded Software, Data Preprocessing, Embedded Systems, Machine Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Data Ethics, Deep Learning, Model Deployment, Convolutional Neural Networks, Data Analysis, Feature Engineering, Computer Programming, Digital Signal Processing

    4.8
    Rating, 4.8 out of 5 stars
    ·
    751 reviews

    Intermediate · Course · 1 - 4 Weeks

  • D

    Duke University

    Bayesian Statistics

    Skills you'll gain: Bayesian Statistics, Statistical Modeling, Statistical Methods, Statistical Inference, Statistical Analysis, Regression Analysis, Data Analysis, R Programming, Probability, Probability Distribution

    3.8
    Rating, 3.8 out of 5 stars
    ·
    798 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Alberta

    A Complete Reinforcement Learning System (Capstone)

    Skills you'll gain: Reinforcement Learning, Artificial Intelligence and Machine Learning (AI/ML), Simulations, Model Evaluation, Performance Testing, Artificial Neural Networks, Machine Learning, Machine Learning Algorithms, Markov Model, Algorithms, Performance Tuning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    650 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    L

    Ludwig-Maximilians-Universität München (LMU)

    Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python

    Skills you'll gain: Finite Element Methods, Numerical Analysis, Engineering Analysis, Jupyter, Engineering Calculations, Differential Equations, Applied Mathematics, Mathematical Modeling, Distributed Computing, Python Programming, Mechanics, Vibrations, Simulations

    4.8
    Rating, 4.8 out of 5 stars
    ·
    391 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    Imperial College London

    Probabilistic Deep Learning with TensorFlow 2

    Skills you'll gain: Tensorflow, Autoencoders, Generative Model Architectures, Deep Learning, Applied Machine Learning, Image Analysis, Bayesian Statistics, Probability Distribution, Unsupervised Learning, Sampling (Statistics)

    4.7
    Rating, 4.7 out of 5 stars
    ·
    109 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    K

    Kennesaw State University

    Six Sigma Tools for Analyze

    Skills you'll gain: Six Sigma Methodology, Lean Six Sigma, Root Cause Analysis, Process Analysis, Probability Distribution, Probability & Statistics, Process Improvement, Quality Improvement, Process Mapping, Systems Of Measurement, Data Analysis, Statistical Methods, Probability, Statistics, Risk Analysis

    4.7
    Rating, 4.7 out of 5 stars
    ·
    1.9K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    P

    Packt

    Data Structures and Algorithms: The Complete Masterclass

    Skills you'll gain: Data Structures, Algorithms, Graph Theory, Programming Principles, Theoretical Computer Science, Computer Science, Computer Programming, Python Programming, Pandas (Python Package), Machine Learning Algorithms, Computational Thinking, C++ (Programming Language), Data Architecture, Random Forest Algorithm, Performance Tuning, Object Oriented Programming (OOP), Network Analysis, Program Development, Problem Solving, Debugging

    4.5
    Rating, 4.5 out of 5 stars
    ·
    37 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Minnesota

    Recommender Systems

    Skills you'll gain: AI Personalization, Model Evaluation, Machine Learning Algorithms, Taxonomy, Decision Support Systems, Business Metrics, Applied Machine Learning, Machine Learning, Dimensionality Reduction, Performance Metric, Spreadsheet Software, Data Collection, Performance Measurement, Benchmarking, Data Validation, Exploratory Data Analysis, A/B Testing, Analysis, User Feedback, Predictive Modeling

    4.3
    Rating, 4.3 out of 5 stars
    ·
    832 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Preview
    Preview
    N

    National Taiwan University

    機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations

    Skills you'll gain: Supervised Learning, Machine Learning, Statistical Machine Learning, Model Evaluation, Logistic Regression, Theoretical Computer Science, Classification Algorithms, Mathematical Theory & Analysis, Probability & Statistics, Algorithms

    4.9
    Rating, 4.9 out of 5 stars
    ·
    937 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    M

    Microsoft

    Microsoft Azure AI Fundamentals AI-900 Exam Prep

    Skills you'll gain: Responsible AI, Image Analysis, Anomaly Detection, Unsupervised Learning, Microsoft Azure, Natural Language Processing, Computer Vision, Artificial Intelligence, Applied Machine Learning, MLOps (Machine Learning Operations), AI Security, Regression Analysis, No-Code Development, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Machine Learning, AI Workflows, Model Deployment, Classification Algorithms, Analytics

    4.5
    Rating, 4.5 out of 5 stars
    ·
    1.5K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Preview
    Preview
    U

    University of Illinois Urbana-Champaign

    VLSI CAD Part I: Logic

    Skills you'll gain: Computational Logic, Application Specific Integrated Circuits, Theoretical Computer Science, Data Structures, Verification And Validation, Computer Architecture, Systems Design, Algorithms, Computer Engineering, Mathematical Software, Design Software, Computer Programming Tools, Debugging, Digital Design, Software Development Tools

    4.6
    Rating, 4.6 out of 5 stars
    ·
    557 reviews

    Intermediate · Course · 1 - 3 Months

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In summary, here are 10 of our most popular random forest algorithm courses

  • Inferential Statistical Analysis with Python: University of Michigan
  • Introduction to Embedded Machine Learning: Edge Impulse
  • Bayesian Statistics: Duke University
  • A Complete Reinforcement Learning System (Capstone): University of Alberta
  • Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python: Ludwig-Maximilians-Universität München (LMU)
  • Probabilistic Deep Learning with TensorFlow 2: Imperial College London
  • Six Sigma Tools for Analyze: Kennesaw State University
  • Data Structures and Algorithms: The Complete Masterclass: Packt
  • Recommender Systems: University of Minnesota
  • 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations: National Taiwan University

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