Random Forest 课程
Random Forest 课程可以帮助您学习决策树算法、Ensemble 方法、Feature Selection 和模型评估技术。您可以掌握数据预处理、超参数调整和解释模型输出的技能。许多课程会介绍 Python 的 Scikit-learn 和 R 的 randomForest 包等工具，展示如何将这些技能应用于分类、回归和处理大型数据集等任务。
热门 Random Forest 课程和认证
状态：免费试用您将获得的技能: NumPy, Plot (Graphics), Pandas (Python Package), Scientific Visualization, Data Manipulation, Scatter Plots, Machine Learning, Data Science, Data Analysis Software, Histogram, Numerical Analysis, Linear Algebra, Probability Distribution, Classification Algorithms, Regression Analysis
状态：预览University of Michigan
您将获得的技能: Sampling (Statistics), Sample Size Determination, Data Collection, Surveys, Statistical Methods, Quantitative Research, Probability & Statistics, Research Design, Statistical Software
状态：免费试用University of Michigan
您将获得的技能: Data Quality, Data Integrity, Data Validation, Data Governance, Quality Assurance, Data Collection, Data Strategy, Data Preprocessing, Data Analysis, Verification And Validation, Design Strategies, Sampling (Statistics)
状态：免费试用University of Colorado Boulder
您将获得的技能: Sampling (Statistics), Estimation, Risk Analysis, Statistical Methods, Statistical Software, Return On Investment, Statistical Analysis, Sample Size Determination, R (Software), Data Analysis, Business Risk Management, Probability & Statistics, Statistical Inference, Project Estimation, Business Analysis
状态：新状态：预览Northeastern University
您将获得的技能: Probability & Statistics, Probability Distribution, Probability, Statistical Methods, Exploratory Data Analysis, Statistical Analysis, Bayesian Statistics, Descriptive Statistics, Data Analysis, Statistical Visualization, Correlation Analysis, Reliability, Risk Modeling
状态：免费试用您将获得的技能: Model Evaluation, Data Manipulation, Python Programming, Probability & Statistics, Applied Machine Learning, Pandas (Python Package), Data Science, Statistical Analysis, NumPy, Machine Learning, Probability Distribution
状态：新状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Natural Language Processing, Embeddings, Hugging Face, Deep Learning, Large Language Modeling, Transfer Learning, Convolutional Neural Networks, Text Mining, Semantic Web, Tensorflow, PyTorch (Machine Learning Library), Artificial Neural Networks, Python Programming, Cryptography, Classification Algorithms, Probability Distribution, Machine Learning Algorithms, Data Processing, Algorithms
状态：免费试用您将获得的技能: Matplotlib, Data Visualization, Probability & Statistics, Plotly, Statistical Analysis, Data Visualization Software, Statistical Hypothesis Testing, Seaborn, Data Science, Programming Principles, Pandas (Python Package), Statistics, Descriptive Statistics, Data Analysis, NumPy, Probability Distribution, Exploratory Data Analysis, Python Programming
状态：新状态：免费试用Johns Hopkins University
您将获得的技能: Trigonometry, Probability, Data Analysis, Algebra, Probability Distribution, Descriptive Statistics, Mathematical Modeling, Graphing, Statistics, Geometry, Arithmetic
状态：预览Fractal Analytics
您将获得的技能: Model Evaluation, Generative AI, Data Preprocessing, Transfer Learning, PyTorch (Machine Learning Library), Machine Learning, Convolutional Neural Networks, Image Quality
状态：新状态：预览O.P. Jindal Global University
您将获得的技能: Sampling (Statistics), Statistical Analysis, Probability Distribution, Statistical Hypothesis Testing, Descriptive Statistics, Statistical Methods, Correlation Analysis, Regression Analysis, R (Software), R Programming, Statistical Modeling, Statistical Inference, Probability, Big Data, Decision Tree Learning
状态：新状态：免费试用University of Pittsburgh
您将获得的技能: Statistical Analysis, Statistical Modeling, Predictive Modeling, Data Analysis, Statistics, Integral Calculus, Probability & Statistics, Data Science, Probability Distribution, Calculus, Mathematics and Mathematical Modeling, Applied Mathematics, Derivatives, Mathematical Modeling, Machine Learning, Algorithms
总之，以下是 10 最受欢迎的 random forest 课程
- NumPy, Matplotlib & Pandas – Data Science Prerequisites: Packt
- Muestreo de personas, redes y registros: University of Michigan
- Design Strategies for Maximizing Total Data Quality: University of Michigan
- Data Acquisition, Risk, and Estimation: University of Colorado Boulder
- Engineering Probability and Statistics Part 1: Northeastern University
- Foundations of ML & Python for Data Science: Packt
- Modern Natural Language Processing: Packt
- Python and Statistics Foundations: Edureka
- Honors Algebra 2: Series, Trigonometry, and Probability: Johns Hopkins University
- How to Build a Diffusion Model - An Introduction: Fractal Analytics
