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  • Random Forest Algorithm


Results for "random+forest+algorithm"


  • Status: New
    New
    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

  • P

    Packt

    Clustering and Classification with Machine Learning in R

    Skills you'll gain: Unsupervised Learning, Dimensionality Reduction, Supervised Learning, R Programming, Applied Machine Learning, R (Software), Classification Algorithms, Machine Learning, Decision Tree Learning, Data Science, Ggplot2, Feature Engineering, Data Preprocessing, Statistical Programming, Predictive Modeling, Data Manipulation, Model Evaluation, Regression Analysis

    Beginner · Course · 1 - 3 Months

  • 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
    V

    Vanderbilt University

    From Data to Decisions: Finding Patterns with AI

    Skills you'll gain: Statistical Methods, Statistical Analysis, Data Visualization, Generative AI, Statistical Hypothesis Testing, Data Presentation, Data Storytelling, Box Plots, Data Analysis, Plot (Graphics), Data-Driven Decision-Making, Statistics, Technical Communication, Statistical Inference, Graphing

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6 reviews

    Beginner · Course · 1 - 4 Weeks

  • 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
    ·
    65 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Principal Component Analysis with NumPy

    Skills you'll gain: Exploratory Data Analysis, NumPy, Data Visualization, Data Analysis, Seaborn, Matplotlib, Statistical Visualization, Jupyter, Dimensionality Reduction, Data Science, Machine Learning Methods, Python Programming, Data Preprocessing

    4.6
    Rating, 4.6 out of 5 stars
    ·
    298 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    C

    CertNexus

    Build Regression, Classification, and Clustering Models

    Skills you'll gain: Model Evaluation, Unsupervised Learning, Regression Analysis, Classification Algorithms, Machine Learning Algorithms, Linear Algebra, Machine Learning, Predictive Modeling, Statistical Modeling, Supervised Learning, Performance Tuning

    4.4
    Rating, 4.4 out of 5 stars
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    18 reviews

    Intermediate · Course · 1 - 3 Months

  • 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: Preview
    Preview
    I

    IIT Roorkee

    Data Mining for Smart Cities

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Data Preprocessing, Anomaly Detection, Data Mining, Applied Machine Learning, Machine Learning Algorithms, Big Data, Data Cleansing, Data Visualization, Python Programming, Data-Driven Decision-Making, Classification Algorithms, Statistical Programming, Exploratory Data Analysis, Deep Learning, Regression Analysis, Artificial Neural Networks

    Beginner · Course · 1 - 3 Months

  • Status: New
    New
    Status: Preview
    Preview
    E

    EDUCBA

    R: Apply & Analyze K-Means Clustering for Unsupervised ML

    Skills you'll gain: Unsupervised Learning, Customer Analysis, Applied Machine Learning, R Programming, Data Preprocessing, Statistical Machine Learning, Machine Learning, Feature Engineering, Data Analysis

    Mixed · Course · 1 - 4 Weeks

  • 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
    ·
    232 reviews

    Intermediate · Guided Project · Less Than 2 Hours

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

    EDUCBA

    AI & Predictive Analytics with Python

    Skills you'll gain: Unsupervised Learning, Predictive Modeling, Supervised Learning, Model Evaluation, Applied Machine Learning, Predictive Analytics, Random Forest Algorithm, Text Mining, Classification Algorithms, Natural Language Processing, Machine Learning Algorithms, Artificial Intelligence, Computational Logic, Python Programming, Data Science, Unstructured Data, Data Preprocessing, Algorithms

    Mixed · Course · 1 - 4 Weeks

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

  • Develop a Movie Recommendation Engine: EDUCBA
  • Clustering and Classification with Machine Learning in R: Packt
  • Deep Learning with R: Build & Predict Neural Networks: EDUCBA
  • From Data to Decisions: Finding Patterns with AI: Vanderbilt University
  • Interpretable Machine Learning Applications: Part 1: Coursera
  • Principal Component Analysis with NumPy: Coursera
  • Build Regression, Classification, and Clustering Models: CertNexus
  • ML Parameters Optimization: GridSearch, Bayesian, Random: Coursera
  • Data Mining for Smart Cities: IIT Roorkee
  • R: Apply & Analyze K-Means Clustering for Unsupervised ML: EDUCBA

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