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。

DeepLearning.AI
您将获得的技能: 模型评估, 数据分析, 机器学习, 自然语言处理, 健康信息学, 深度学习, 统计分析, 医学术语, 临床试验, 应用机器学习, 病人治疗, 治疗计划, AI 个性化服务, 文本挖掘
中级 · 课程 · 1-4 周

DeepLearning.AI
您将获得的技能: 模型评估, 数据分析, 逻辑回归, 数据预处理, 机器学习, 概率与统计, 深度学习, 随机森林算法, 预测建模, 统计分析, 决策树学习, 风险模型, 应用机器学习, 预测, 功能工程
中级 · 课程 · 1-4 周

您将获得的技能: 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
混合 · 课程 · 1-4 周

您将获得的技能: Dimensionality Reduction, Unsupervised Learning, Deep Learning, Model Evaluation, Machine Learning Algorithms, Applied Machine Learning, Random Forest Algorithm, Feature Engineering, Artificial Neural Networks, Supervised Learning, Statistical Machine Learning, Anomaly Detection, Classification Algorithms, Performance Tuning
中级 · 课程 · 1-3 个月

Arizona State University
您将获得的技能: 概率分布, 统计建模, 回归分析, 统计方法, 抽样(统计), 统计分析, 数据分析软件, 数据转换, 统计假设检验
中级 · 课程 · 1-4 周

您将获得的技能: Unsupervised Learning, Dimensionality Reduction, Supervised Learning, R Programming, Applied Machine Learning, R (Software), Classification Algorithms, Machine Learning, Decision Tree Learning, Data Science, Ggplot2, Feature Engineering, Data Preprocessing, Statistical Programming, Predictive Modeling, Data Manipulation, Model Evaluation, Regression Analysis
初级 · 课程 · 1-3 个月

Johns Hopkins University
您将获得的技能: Model Evaluation, Unsupervised Learning, Applied Machine Learning, Dimensionality Reduction, Reinforcement Learning, Regression Analysis, Machine Learning, Data Mining, Machine Learning Algorithms, Random Forest Algorithm, Decision Tree Learning, Supervised Learning, Logistic Regression, Classification Algorithms
中级 · 课程 · 1-3 个月

您将获得的技能: Unsupervised Learning, Predictive Modeling, Supervised Learning, Model Evaluation, Applied Machine Learning, Predictive Analytics, Random Forest Algorithm, Text Mining, Classification Algorithms, Natural Language Processing, Machine Learning Algorithms, Artificial Intelligence, Computational Logic, Python Programming, Data Science, Unstructured Data, Data Preprocessing, Algorithms
混合 · 课程 · 1-4 周

Duke University
您将获得的技能: 模型评估, 卷积神经网络, 数据科学, 计算机视觉, 逻辑回归, 分类与回归树 (CART), 机器学习, 监督学习, 自然语言处理, 人工智能和机器学习(AI/ML), 随机森林算法, 回归分析, 深度学习, 预测分析, 决策树学习, 无监督学习, Algorithm
中级 · 课程 · 1-3 个月

您将获得的技能: Scikit Learn (Machine Learning Library), Classification Algorithms, Applied Machine Learning, Machine Learning Algorithms, Supervised Learning, Random Forest Algorithm, Machine Learning, Unsupervised Learning, Data Analysis
初级 · 指导项目 · 不超过 2 小时

您将获得的技能: Machine Learning Algorithms, Data Visualization, Dashboard, Classification Algorithms, Interactive Data Visualization, Data Visualization Software, Model Evaluation, Machine Learning, Scikit Learn (Machine Learning Library), Plot (Graphics), Web Applications, Logistic Regression, Predictive Modeling, Data Science, Python Programming, Pandas (Python Package)
中级 · 指导项目 · 不超过 2 小时
Stanford University
您将获得的技能: 概率分布, 统计方法, 概率与统计, 计算思维, 应用机器学习, 抽样(统计), 统计推理, 贝叶斯网络, Machine Learning 方法, 机器学习算法, 马尔可夫模型, 图论, Algorithm
高级设置 · 课程 · 1-3 个月