Filter by
SubjectRequired
LanguageRequired
The language used throughout the course, in both instruction and assessments.
Learning ProductRequired
LevelRequired
DurationRequired
SkillsRequired
SubtitlesRequired
EducatorRequired
Results for "random forests"
- Status: New
Johns Hopkins University
Skills you'll gain: Probability, Bayesian Statistics, Probability Distribution, Risk Modeling, Mathematical Modeling, Statistical Inference, Markov Model, Reliability, Simulations, Applied Mathematics, Statistical Analysis, Regression Analysis
University of Maryland, College Park
Skills you'll gain: Statistical Analysis, Statistical Software, Data Integration, Data Ethics, Stata, R Programming, Sampling (Statistics), Statistical Modeling, Descriptive Statistics, Regression Analysis, Probability & Statistics, Information Privacy
- Status: Free
EIT Digital
Skills you'll gain: Data Structures, Theoretical Computer Science, Data Storage Technologies, Algorithms, Graph Theory, File Systems, Data Access, Performance Tuning, Analysis
- Status: New
University of Michigan
Skills you'll gain: Debugging, NumPy, Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Pandas (Python Package), Data Structures, Probability & Statistics, Statistical Methods, Probability, Statistics, Probability Distribution, Statistical Analysis, Data Analysis, Program Development, Large Language Modeling, Data Manipulation, Programming Principles, Computer Programming, Python Programming
University of Pennsylvania
Skills you'll gain: Probability, Probability & Statistics, Sampling (Statistics), Probability Distribution, Statistics, Data Science, Statistical Inference, Descriptive Statistics, Statistical Analysis, General Mathematics
Coursera Project Network
Skills you'll gain: MLOps (Machine Learning Operations), Continuous Deployment, Application Deployment, Tidyverse (R Package), R Programming, Dashboard, Health Informatics, Applied Machine Learning, Continuous Monitoring, Predictive Modeling, Machine Learning Methods, Statistical Machine Learning, Docker (Software), Application Programming Interface (API)
Illinois Tech
Skills you'll gain: Bayesian Statistics, Data Analysis, Statistical Modeling, Statistical Analysis, Statistical Programming, Statistical Methods, Regression Analysis, Statistical Inference, R Programming, Numerical Analysis, Markov Model, Probability, Simulations, Probability Distribution
- Status: Free
EIT Digital
Skills you'll gain: Computational Logic, Markov Model, Verification And Validation, Theoretical Computer Science, Mathematical Modeling, Systems Analysis, Probability, Algorithms, Real-Time Operating Systems, Probability Distribution
- Status: Free
Coursera Project Network
Skills you'll gain: Keras (Neural Network Library), Artificial Neural Networks, Applied Machine Learning, Deep Learning, Python Programming, Performance Tuning, Machine Learning Algorithms
Johns Hopkins University
Skills you'll gain: Surveys, Survey Creation, Sampling (Statistics), Quantitative Research, Research Methodologies, Data Analysis, Data Quality, Data Transformation, Data Modeling, Data Validation, Statistical Methods
- Status: Free
National Taiwan University
Skills you'll gain: Feature Engineering, Classification And Regression Tree (CART), Statistical Machine Learning, Supervised Learning, Machine Learning Algorithms, Random Forest Algorithm, Deep Learning, Machine Learning, Applied Machine Learning, Artificial Neural Networks, Dimensionality Reduction, Regression Analysis
University of Colorado Boulder
Skills you'll gain: Process Capability, Statistical Process Controls, Statistical Analysis, Data Analysis Software, R Programming, Quality Control, Statistical Methods, Process Analysis, Data Transformation, Statistical Hypothesis Testing, Process Improvement, Probability Distribution
Searches related to random forests
In summary, here are 10 of our most popular random forests courses
- Introduction to Uncertainty Quantification:Â Johns Hopkins University
- Combining and Analyzing Complex Data:Â University of Maryland, College Park
- I/O-efficient algorithms:Â EIT Digital
- Data-Oriented Python Programming and Debugging:Â University of Michigan
- Statistics for Data Science Essentials:Â University of Pennsylvania
- MLOps in R: Deploying machine learning models using vetiver:Â Coursera Project Network
- Bayesian Computational Statistics:Â Illinois Tech
- Quantitative Model Checking:Â EIT Digital
- Hyperparameter Tuning with Keras Tuner:Â Coursera Project Network
- Measurement – Turning Concepts into Data: Johns Hopkins University