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  • Random Forest Algorithm

Results for "random+forest+algorithm"


  • P

    Packt

    Master Retrieval-Augmented Generation (RAG) Systems

    Skills you'll gain: Retrieval-Augmented Generation, Embeddings, Large Language Modeling, Plot (Graphics), Generative AI, Vector Databases, LLM Application, Text Mining, Dimensionality Reduction

    ★ 4.2 (6) · Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    TensorFlow Prediction: Identify Penguin Species

    Skills you'll gain: Model Evaluation, Data Preprocessing, Model Training, Tensorflow, Applied Machine Learning, Feature Engineering, Decision Tree Learning, Data Cleansing, Machine Learning, Predictive Modeling, Random Forest Algorithm, Pandas (Python Package), Data Analysis

    Intermediate · Guided Project · Less Than 2 Hours

    Category: Credit offered
    Credit offered
  • C

    Coursera

    Traverse Trees for ML with DFS & BFS

    Skills you'll gain: Classification And Regression Tree (CART), Decision Tree Learning, Classification Algorithms, Applied Machine Learning, Java Programming, Machine Learning Algorithms, Algorithms, Machine Learning, Data Structures, Analysis, Software Engineering

    Advanced · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Solve Tree Problems with Java Recursion

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

    Advanced · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    ML Parameters Optimization: GridSearch, Bayesian, Random

    Skills you'll gain: Model Optimization, Model Evaluation, Scikit Learn (Machine Learning Library), Regression Analysis, Fine-tuning, Applied Machine Learning, Machine Learning, Data Analysis

    ★ 4.9 (8) · Beginner · Guided Project · Less Than 2 Hours

    Category: Credit offered
    Credit offered
  • C

    Coursera

    Interpretable Machine Learning Applications: Part 1

    Skills you'll gain: Model Training, Feature Engineering, Classification And Regression Tree (CART), Decision Tree Learning, Applied Machine Learning, Model Evaluation, Random Forest Algorithm, Responsible AI, Predictive Modeling, Data Preprocessing, Data Import/Export, Machine Learning, Classification Algorithms

    ★ 4.5 (98) · Beginner · Guided Project · Less Than 2 Hours

    Category: Credit offered
    Credit offered
  • P

    Packt

    Intermediate Algorithms: Graphs, Trees, and Backtracking

    Skills you'll gain: Data Structures, Graph Theory, Algorithms

    Intermediate · Course · 1 - 3 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • U

    University of Colorado Boulder

    Trees, SVM and Unsupervised Learning

    Skills you'll gain: Model Evaluation, Applied Machine Learning, Unsupervised Learning, Decision Tree Learning, Artificial Neural Networks, Machine Learning Methods, Classification Algorithms, Supervised Learning, Statistical Machine Learning, Machine Learning Algorithms, Random Forest Algorithm, Predictive Modeling, Applied Mathematics, Dimensionality Reduction, Statistics

    ★ 4.4 (9) · Intermediate · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • C

    Coursera

    Decision Tree Classifier for Beginners in R

    Skills you'll gain: Model Evaluation, Model Training, Classification And Regression Tree (CART), Decision Tree Learning, Data Preprocessing, R (Software), Statistical Modeling, R Programming, Supervised Learning, Machine Learning

    ★ 4.8 (6) · Beginner · Guided Project · Less Than 2 Hours

    Category: Credit offered
    Credit offered
  • U

    University of Washington

    Machine Learning: Clustering & Retrieval

    Skills you'll gain: Unsupervised Learning, Bayesian Statistics, Applied Machine Learning, Data Mining, Statistical Machine Learning, Statistical Inference, Text Mining, Machine Learning Methods, Statistical Modeling, Machine Learning Algorithms, Unstructured Data, Machine Learning, Sampling (Statistics), Scalability, Distributed Computing, Probability Distribution, Algorithms

    ★ 4.6 (2.4K) · Mixed · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • D

    DeepLearning.AI

    Advanced Learning Algorithms

    Skills you'll gain: Model Training, Machine Learning Algorithms, Transfer Learning, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Responsible AI, Supervised Learning, Deep Learning, Classification Algorithms, Random Forest Algorithm, Model Optimization, Artificial Neural Networks, Logistic Regression, Regression Analysis

    ★ 4.9 (8.7K) · Beginner · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • P

    Packt

    No-Code Machine Learning Using Amazon AWS SageMaker Canvas

    Skills you'll gain: AWS SageMaker, Applied Machine Learning, Model Evaluation, Amazon Web Services, Machine Learning Methods, No-Code Development, Model Training, Machine Learning, Machine Learning Algorithms, Supervised Learning, Cloud Platforms, Predictive Modeling, Amazon S3, Version Control, Data Preprocessing, Model Deployment, Data Import/Export, Data Validation

    Beginner · Course · 1 - 3 Months

    Category: Credit offered
    Credit offered
1…678…9

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

  • Master Retrieval-Augmented Generation (RAG) Systems: Packt
  • TensorFlow Prediction: Identify Penguin Species: Coursera
  • Traverse Trees for ML with DFS & BFS: Coursera
  • Solve Tree Problems with Java Recursion: Coursera
  • ML Parameters Optimization: GridSearch, Bayesian, Random: Coursera
  • Interpretable Machine Learning Applications: Part 1: Coursera
  • Intermediate Algorithms: Graphs, Trees, and Backtracking: Packt
  • Trees, SVM and Unsupervised Learning: University of Colorado Boulder
  • Decision Tree Classifier for Beginners in R: Coursera
  • Machine Learning: Clustering & Retrieval: University of Washington

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