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  • Random Forest Algorithm

Results for "random+forest+algorithm"


  • C

    Coursera

    Classification Trees in Python, From Start To Finish

    Skills you'll gain: Decision Tree Learning, Data Preprocessing, Data Transformation, Supervised Learning, Feature Engineering, Scikit Learn (Machine Learning Library), Classification Algorithms, Model Evaluation, Pandas (Python Package)

    4.6
    Rating, 4.6 out of 5 stars
    ·
    233 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Solve Tree Problems with Java Recursion

    Skills you'll gain: Performance Tuning, Java, Enterprise Application Management, Computational Thinking, Algorithms, Data Structures, Scalability, Programming Principles, Debugging, Management Consulting, Mitigation, Project Implementation

    Advanced · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Preview
    Preview
    E

    EDUCBA

    Deep Learning with R: Build & Predict Neural Networks

    Skills you'll gain: Plot (Graphics), Data Visualization Software, R Programming, Scatter Plots, Regression Analysis, Statistical Modeling, Predictive Modeling, Artificial Neural Networks, Data Science, Deep Learning, Model Evaluation, Descriptive Statistics, Predictive Analytics, Statistical Methods, Data Manipulation, Data Preprocessing, Performance Testing

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    P

    Packt

    Advanced ML Algorithms & Unsupervised Learning

    Skills you'll gain: Dimensionality Reduction, Unsupervised Learning, Deep Learning, Model Evaluation, Machine Learning Algorithms, Applied Machine Learning, Random Forest Algorithm, Feature Engineering, Artificial Neural Networks, Supervised Learning, Statistical Machine Learning, Anomaly Detection, Classification Algorithms, Performance Tuning

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    MLOps Platforms: Amazon SageMaker and Azure ML

    Skills you'll gain: AWS SageMaker, MLOps (Machine Learning Operations), Microsoft Azure, Model Deployment, Exploratory Data Analysis, Data Pipelines, Amazon Web Services, Feature Engineering, Cloud Solutions, Model Evaluation, Data Preprocessing, Cloud Deployment, Data Analysis, Serverless Computing, Machine Learning, Python Programming

    3.6
    Rating, 3.6 out of 5 stars
    ·
    55 reviews

    Advanced · Course · 1 - 3 Months

  • C

    Coursera

    Interpretable Machine Learning Applications: Part 1

    Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Model Evaluation, Random Forest Algorithm, Responsible AI, Data Import/Export, Machine Learning, Classification Algorithms

    4.4
    Rating, 4.4 out of 5 stars
    ·
    77 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    ML Parameters Optimization: GridSearch, Bayesian, Random

    Skills you'll gain: Model Evaluation, Scikit Learn (Machine Learning Library), Regression Analysis, Performance Tuning, Applied Machine Learning, Machine Learning Methods, Machine Learning, Bayesian Statistics, Data Analysis

    4.9
    Rating, 4.9 out of 5 stars
    ·
    8 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    PySpark: Apply & Evaluate Predictive ML Models

    Skills you'll gain: Model Evaluation, PySpark, Apache Spark, Logistic Regression, Predictive Modeling, Applied Machine Learning, Unsupervised Learning, Decision Tree Learning, Predictive Analytics, Random Forest Algorithm, Regression Analysis, Classification Algorithms, Machine Learning Algorithms, Data Pipelines

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Alberta

    Sample-based Learning Methods

    Skills you'll gain: Reinforcement Learning, Sampling (Statistics), Machine Learning Algorithms, Simulations, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Algorithms, Probability Distribution

    4.8
    Rating, 4.8 out of 5 stars
    ·
    1.3K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    F

    Fractal Analytics

    Advanced Machine Learning Algorithms

    Skills you'll gain: Feature Engineering, Model Evaluation, Machine Learning Algorithms, Random Forest Algorithm, Algorithms, Supervised Learning, Applied Machine Learning, Decision Tree Learning, Predictive Modeling, Classification Algorithms, Regression Analysis, Performance Tuning

    3.8
    Rating, 3.8 out of 5 stars
    ·
    12 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Develop a Movie Recommendation Engine

    Skills you'll gain: Feature Engineering, Applied Machine Learning, Machine Learning, Data Preprocessing, Python Programming, Predictive Modeling, Development Environment, Data Manipulation, Exploratory Data Analysis

    4.8
    Rating, 4.8 out of 5 stars
    ·
    10 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Machine Learning with R: Build, Analyze & Predict

    Skills you'll gain: Data Analysis, Statistical Analysis, Probability Distribution, R Programming, Exploratory Data Analysis, Statistical Modeling, Machine Learning, Statistical Inference, Classification Algorithms, Data Manipulation, Supervised Learning, Random Forest Algorithm, Regression Analysis, Model Evaluation, Decision Tree Learning

    4.5
    Rating, 4.5 out of 5 stars
    ·
    15 reviews

    Mixed · Course · 1 - 4 Weeks

1…678…9

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

  • Classification Trees in Python, From Start To Finish: Coursera
  • Solve Tree Problems with Java Recursion: Coursera
  • Deep Learning with R: Build & Predict Neural Networks: EDUCBA
  • Advanced ML Algorithms & Unsupervised Learning: Packt
  • MLOps Platforms: Amazon SageMaker and Azure ML: Duke University
  • Interpretable Machine Learning Applications: Part 1: Coursera
  • ML Parameters Optimization: GridSearch, Bayesian, Random: Coursera
  • PySpark: Apply & Evaluate Predictive ML Models: EDUCBA
  • Sample-based Learning Methods: University of Alberta
  • Advanced Machine Learning Algorithms: Fractal Analytics

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