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  • Random Forest

Results for "random+forest"


  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Applied Unsupervised Learning in Python

    Skills you'll gain: Unsupervised Learning, Embeddings, Supervised Learning, Data Preprocessing, Python Programming, Exploratory Data Analysis

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    G

    Google

    The Nuts and Bolts of Machine Learning

    Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Random Forest Algorithm, Data Analysis, Predictive Modeling, Model Evaluation, Bayesian Network, Python Programming, Statistical Modeling, Classification Algorithms

    4.8
    Rating, 4.8 out of 5 stars
    ·
    613 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Preview
    Preview
    J

    Johns Hopkins University

    Random Processes

    Skills you'll gain: Probability & Statistics, Probability Distribution, Simulations, Statistical Modeling, Correlation Analysis, Engineering Analysis, Digital Signal Processing, Statistical Analysis, Reliability, Engineering, Spatial Analysis

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Foundations of Probability and Random Variables

    Skills you'll gain: R Programming, Statistical Analysis, Statistical Programming, Data Analysis, Probability, Probability Distribution, Applied Machine Learning, Probability & Statistics, Applied Mathematics, Data Science, Computational Thinking, Simulations

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Pittsburgh

    Probability Theory and Regression for Predictive Analytics

    Skills you'll gain: Probability Distribution, Data Science, Probability & Statistics, Predictive Analytics, Probability, Statistical Modeling, Data Analysis, Regression Analysis, Logistic Regression, Statistical Analysis, Statistical Methods, Statistical Machine Learning, Bayesian Statistics, Statistical Inference, Feature Engineering, Applied Mathematics, Python Programming, Machine Learning, Algorithms

    Build toward a degree

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    Duke University

    DevOps, DataOps, MLOps

    Skills you'll gain: MLOps (Machine Learning Operations), Responsible AI, Artificial Intelligence and Machine Learning (AI/ML), PyTorch (Machine Learning Library), Containerization, Tensorflow, Rust (Programming Language), Microsoft Copilot, DevOps, Hugging Face, Applied Machine Learning, Cloud Solutions, CI/CD, Machine Learning, Serverless Computing, Docker (Software), GitHub, Big Data

    4.1
    Rating, 4.1 out of 5 stars
    ·
    217 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    W

    Whizlabs

    NVIDIA: Prompt Engineering and Data Analysis

    Skills you'll gain: Prompt Engineering, Plot (Graphics), Data Visualization, Large Language Modeling, Text Mining, Retrieval-Augmented Generation, Data Visualization Software, Data Analysis, Natural Language Processing

    5
    Rating, 5 out of 5 stars
    ·
    6 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    E

    EDUCBA

    R: Design & Evaluate Random Forests for Attrition

    Skills you'll gain: Model Evaluation, Data Preprocessing, Workforce Management, Advanced Analytics, Classification Algorithms

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    P

    Packt

    Deep Learning: Recurrent Neural Networks with Python

    Skills you'll gain: Model Deployment, PyTorch (Machine Learning Library), Recurrent Neural Networks (RNNs), Tensorflow, Artificial Intelligence, Applied Machine Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Text Mining, Machine Learning, Natural Language Processing, Deep Learning, Predictive Modeling, Classification Algorithms, Supervised Learning, Time Series Analysis and Forecasting, Network Architecture, Data Science, Model Evaluation

    Beginner · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    Duke University

    Introduction to Probability and Data with R

    Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, R (Software), Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Analysis, Descriptive Statistics

    4.7
    Rating, 4.7 out of 5 stars
    ·
    5.9K reviews

    Beginner · Course · 1 - 3 Months

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

    EDUCBA

    AI Machine Learning with R & Python Projects

    Skills you'll gain: Sampling (Statistics), Matplotlib, Data Analysis, Data Mining, Statistical Analysis, Statistical Hypothesis Testing, NumPy, Pandas (Python Package), Probability Distribution, Dimensionality Reduction, Model Evaluation, R Programming, Probability, Python Programming, Scikit Learn (Machine Learning Library), Data Preprocessing, Linear Algebra, Applied Machine Learning, Regression Analysis, Artificial Intelligence and Machine Learning (AI/ML)

    4.5
    Rating, 4.5 out of 5 stars
    ·
    17 reviews

    Beginner · Specialization · 3 - 6 Months

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

    Coursera

    Build Robust Java ML Models with Entropy

    Skills you'll gain: Model Evaluation, Model Deployment, Decision Tree Learning, Data Preprocessing, Classification Algorithms, Predictive Modeling, Random Forest Algorithm, Applied Machine Learning, Java, Program Evaluation, Machine Learning, Feature Engineering, Algorithms, Program Implementation, Business Development

    Advanced · Course · 1 - 4 Weeks

1234…9

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

  • Applied Unsupervised Learning in Python: University of Michigan
  • The Nuts and Bolts of Machine Learning: Google
  • Random Processes: Johns Hopkins University
  • Foundations of Probability and Random Variables: Johns Hopkins University
  • Probability Theory and Regression for Predictive Analytics: University of Pittsburgh
  • DevOps, DataOps, MLOps: Duke University
  • NVIDIA: Prompt Engineering and Data Analysis: Whizlabs
  • R: Design & Evaluate Random Forests for Attrition: EDUCBA
  • Deep Learning: Recurrent Neural Networks with Python: Packt
  • Introduction to Probability and Data with R: Duke University

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