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  • Random Forest Algorithm

Results for "random+forest+algorithm"


  • C

    Coursera

    Decision Tree Classifier for Beginners in R

    Skills you'll gain: Model Evaluation, Decision Tree Learning, Data Preprocessing, Data Manipulation, Statistical Modeling, R Programming, Supervised Learning, Machine Learning, Classification Algorithms

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6 reviews

    Beginner · Guided Project · Less Than 2 Hours

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

    EDUCBA

    Machine Learning with Python: Build & Optimize

    Skills you'll gain: Matplotlib, Data Preprocessing, Regression Analysis, Scikit Learn (Machine Learning Library), Data Visualization, Python Programming, Applied Machine Learning, Pandas (Python Package), Model Evaluation, NumPy, Predictive Modeling, Machine Learning Algorithms, Machine Learning, Data Manipulation, Dimensionality Reduction, Statistical Methods, Data Transformation, Feature Engineering, Unsupervised Learning, Performance Tuning

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Illinois Urbana-Champaign

    Machine Learning Algorithms with Python in Business Analytics

    Skills you'll gain: Classification Algorithms, Business Analytics, Data Preprocessing, Regression Analysis, Applied Machine Learning, Scikit Learn (Machine Learning Library), Unsupervised Learning, Business Intelligence, Predictive Modeling, Machine Learning, Python Programming, Decision Tree Learning, Supervised Learning, Model Evaluation

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    41 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free
    Free
    C

    Coursera

    Machine Learning with PySpark: Recommender System

    Skills you'll gain: PySpark, Apache Spark, Data Pipelines, Data Processing, AI Personalization, Dimensionality Reduction, OpenAI API, Data Manipulation, Pandas (Python Package), Data Transformation, Predictive Modeling, Unsupervised Learning, Applied Machine Learning, Scatter Plots, Embeddings, Machine Learning

    Intermediate · 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

  • 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

  • Status: Free
    Free
    C

    Coursera

    TensorFlow Prediction: Identify Penguin Species

    Skills you'll gain: Model Evaluation, Data Preprocessing, Tensorflow, Applied Machine Learning, Feature Engineering, Data Cleansing, Classification And Regression Tree (CART), Machine Learning, Random Forest Algorithm, Pandas (Python Package), Data Analysis, Exploratory Data Analysis

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    P

    Packt

    Exploratory Data Analysis & Core ML Algorithms

    Skills you'll gain: Exploratory Data Analysis, Predictive Modeling, Decision Tree Learning, Data Analysis, Regression Analysis, Classification Algorithms, Supervised Learning, Machine Learning Algorithms, Model Evaluation, Scikit Learn (Machine Learning Library), Data Preprocessing, Statistical Machine Learning, Feature Engineering

    Intermediate · Course · 1 - 3 Months

  • 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

  • 2

    28DIGITAL

    I/O-efficient algorithms

    Skills you'll gain: File I/O, Data Structures, Theoretical Computer Science, Data Storage Technologies, Algorithms, Graph Theory, Data Access, Performance Tuning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    60 reviews

    Advanced · Course · 1 - 3 Months

  • 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
    ·
    18 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of California San Diego

    Machine Learning With Big Data

    Skills you'll gain: Model Evaluation, Exploratory Data Analysis, Apache Spark, Classification Algorithms, Big Data, Regression Analysis, Data Mining, Applied Machine Learning, Data Preprocessing, Statistical Analysis, Machine Learning, Data Analysis, Unsupervised Learning, Predictive Modeling, Supervised Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.5K reviews

    Mixed · Course · 1 - 3 Months

1…6789

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

  • Decision Tree Classifier for Beginners in R: Coursera
  • Machine Learning with Python: Build & Optimize: EDUCBA
  • Machine Learning Algorithms with Python in Business Analytics: University of Illinois Urbana-Champaign
  • Machine Learning with PySpark: Recommender System: Coursera
  • ML Parameters Optimization: GridSearch, Bayesian, Random: Coursera
  • Interpretable Machine Learning Applications: Part 1: Coursera
  • TensorFlow Prediction: Identify Penguin Species: Coursera
  • Exploratory Data Analysis & Core ML Algorithms: Packt
  • Classification Trees in Python, From Start To Finish: Coursera
  • I/O-efficient algorithms: 28DIGITAL

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