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Results for "random+forests"


  • Status: Free Trial
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    J

    Johns Hopkins University

    Machine Learning and Emerging Technologies in Cybersecurity

    Skills you'll gain: Model Evaluation, Intrusion Detection and Prevention, Threat Detection, Computer Security Incident Management, Cybersecurity, Anomaly Detection, Applied Machine Learning, Network Security, Machine Learning, Unsupervised Learning, Supervised Learning, Artificial Neural Networks

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    S

    Simplilearn

    Supervised Learning Regression Classification Clustering

    Skills you'll gain: Supervised Learning, Data Modeling, Unsupervised Learning, Applied Machine Learning, Data Analysis, Regression Analysis, Classification Algorithms, Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Decision Tree Learning, Predictive Analytics, Logistic Regression, Random Forest Algorithm, Bayesian Statistics

    Beginner · Course · 1 - 4 Weeks

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

    Coursera

    Parse & Normalize Data for ML Pipelines

    Skills you'll gain: Data Preprocessing, Data Pipelines, Java, Data Processing, Feature Engineering, Data Cleansing, Data Quality, Data Transformation, Data Validation, Data Access, Continuous Monitoring, Unit Testing, Object Oriented Programming (OOP)

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Python: Logistic Regression & Supervised ML

    Skills you'll gain: Model Evaluation, Feature Engineering, Supervised Learning, Exploratory Data Analysis, Classification Algorithms, Machine Learning Algorithms, Applied Machine Learning, Decision Tree Learning, Logistic Regression, Predictive Modeling, Data Analysis, Scikit Learn (Machine Learning Library), Data Preprocessing, Pandas (Python Package), NumPy, Data Cleansing

    4.4
    Rating, 4.4 out of 5 stars
    ·
    17 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: New
    New
    P

    Packt

    Real-world End to End Machine Learning Ops on Google Cloud

    Skills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, Generative AI, Model Deployment, Cloud Management, Kubernetes, Large Language Modeling, CI/CD, Cloud Deployment, Machine Learning Methods, Continuous Deployment, Tensorflow, Model Evaluation, Apache Airflow, AI Workflows, Continuous Integration, Feature Engineering, Containerization, Performance Tuning

    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

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Linear Regression & Supervised Learning in Python

    Skills you'll gain: Model Evaluation, Exploratory Data Analysis, Regression Analysis, Predictive Modeling, Supervised Learning, Scikit Learn (Machine Learning Library), Data Analysis, Correlation Analysis, Applied Machine Learning, Scatter Plots, Statistical Analysis, Data Validation, Data Preprocessing, NumPy, Pandas (Python Package), Box Plots, Histogram

    4.6
    Rating, 4.6 out of 5 stars
    ·
    14 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    P

    Packt

    Foundations of ML & Python for Data Science

    Skills you'll gain: Model Evaluation, Data Manipulation, Python Programming, Probability & Statistics, Applied Machine Learning, Pandas (Python Package), Data Science, Statistical Analysis, NumPy, Machine Learning, Probability Distribution

    Beginner · Course · 1 - 4 Weeks

  • I

    IBM

    Scalable Machine Learning on Big Data using Apache Spark

    Skills you'll gain: Apache Spark, PySpark, Applied Machine Learning, Big Data, Machine Learning Methods, Data Storage Technologies, Data Preprocessing, Data Storage, Machine Learning Algorithms, Machine Learning, Distributed Computing, Data Processing, Data Science, Statistical Methods, Model Evaluation, Descriptive Statistics

    3.8
    Rating, 3.8 out of 5 stars
    ·
    1.3K reviews

    Intermediate · Course · 1 - 4 Weeks

  • 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

    5
    Rating, 5 out of 5 stars
    ·
    10 reviews

    Mixed · Course · 1 - 4 Weeks

  • 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

  • C

    Coursera

    Support Vector Machines in Python, From Start to Finish

    Skills you'll gain: Scikit Learn (Machine Learning Library), Tensorflow, Classification Algorithms, Supervised Learning, Applied Machine Learning, Python Programming, Feature Engineering, Data Preprocessing, Data Science, Machine Learning, Model Evaluation, Data Manipulation, Data Visualization

    4.6
    Rating, 4.6 out of 5 stars
    ·
    162 reviews

    Intermediate · Guided Project · Less Than 2 Hours

1…567…9

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

  • Machine Learning and Emerging Technologies in Cybersecurity: Johns Hopkins University
  • Supervised Learning Regression Classification Clustering: Simplilearn
  • Parse & Normalize Data for ML Pipelines: Coursera
  • Python: Logistic Regression & Supervised ML: EDUCBA
  • Real-world End to End Machine Learning Ops on Google Cloud: Packt
  • Classification Trees in Python, From Start To Finish: Coursera
  • Linear Regression & Supervised Learning in Python: EDUCBA
  • Foundations of ML & Python for Data Science: Packt
  • Scalable Machine Learning on Big Data using Apache Spark: IBM
  • PySpark: Apply & Evaluate Predictive ML Models: EDUCBA

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