督导学习课程
监督学习课程可以帮助您学习 Regression 分析、分类技术和模型评估方法。您可以掌握 Feature Selection、Hyperparameter 调整和理解偏差-方差权衡等方面的技能。许多课程都会介绍 Scikit-learn 和 TensorFlow 等 Python 库等工具，这些工具支持算法的实施和数据分析。
受欢迎的监督学习课程和证书
状态：免费试用DeepLearning.AI
您将获得的技能: 机器学习, Python 程序设计, 预测建模, 回归分析, 数据转换, 应用机器学习, NumPy, 人工智能, 分类与回归树 (CART), 统计建模, Scikit-learn （机器学习库）, Jupyter, 功能工程, 监督学习
状态：免费试用您将获得的技能: 机器学习, 预测建模, 回归分析, Scikit-learn （机器学习库）, 降维, 决策树学习, 统计建模, 应用机器学习, 无监督学习, 功能工程, 分类与回归树 (CART), 监督学习
状态：新状态：免费试用Dartmouth College
您将获得的技能: Supervised Learning, Bayesian Network, Artificial Neural Networks, Predictive Analytics, Machine Learning Methods, Statistical Modeling, Predictive Modeling, Statistical Machine Learning, Probability & Statistics, Bayesian Statistics, Deep Learning, Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Applied Machine Learning, Statistical Methods, Artificial Intelligence, Regression Analysis, Statistical Inference
状态：新状态：免费试用Dartmouth College
您将获得的技能: Supervised Learning, Predictive Modeling, Predictive Analytics, Statistical Modeling, Machine Learning, Machine Learning Algorithms, Regression Analysis, Probability & Statistics, Linear Algebra
状态：免费试用多位教师
您将获得的技能: 机器学习, Python 程序设计, 深度学习, 预测建模, 负责任的人工智能, 人工智能和机器学习（AI/ML）, 数据伦理, NumPy, 应用机器学习, 强化学习, 随机森林算法, 人工智能, 决策树学习, Jupyter, 监督学习, 分类与回归树 (CART), 功能工程, 无监督学习, 张力流, Scikit-learn （机器学习库）
状态：免费试用University of Colorado Boulder
您将获得的技能: Python 程序设计, 机器学习, 机器学习算法, 预测建模, 数据科学, 回归分析, 随机森林算法, 统计编程, 数据清理, 应用数学, 探索性数据分析, 数学建模, 功能工程, 决策树学习, 分类与回归树 (CART), Matplotlib, 性能调整, 应用机器学习, 监督学习, Scikit-learn （机器学习库）
是什么让您今天来到 Coursera？
状态：免费试用您将获得的技能: Supervised Learning, Data Modeling, Unsupervised Learning, Applied Machine Learning, Data Analysis, Regression Analysis, Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Predictive Modeling, Random Forest Algorithm, Bayesian Statistics
状态：免费试用Imperial College London
您将获得的技能: 机器学习, Python 程序设计, 回归分析, Algorithm, 数据操作, 线性代数, 机器学习算法, 统计分析, 统计, 微积分, 数据科学, 人工神经网络, NumPy, 概率与统计, 降维, 应用数学, Jupyter, 衍生产品, 高等数学
状态：免费试用Johns Hopkins University
您将获得的技能: Computer Vision, PyTorch (Machine Learning Library), Supervised Learning, Unsupervised Learning, Image Analysis, Applied Machine Learning, Dimensionality Reduction, Reinforcement Learning, Feature Engineering, Machine Learning Algorithms, Regression Analysis, Data Processing, Machine Learning, Predictive Modeling, Data Mining, Data Cleansing, Statistical Machine Learning, Deep Learning, Artificial Neural Networks, Decision Tree Learning
状态：免费试用DeepLearning.AI
您将获得的技能: 机器学习, Algorithm, 深度学习, 数据伦理, 异常检测, 人工智能和机器学习（AI/ML）, 强化学习, 人工智能, 降维, 无监督学习, 应用机器学习, 监督学习
状态：新状态：免费试用您将获得的技能: Feature Engineering, Microsoft Azure, Applied Machine Learning, Machine Learning, Machine Learning Algorithms, Data Processing, Data Cleansing, Supervised Learning, Data Transformation, MLOps (Machine Learning Operations), Application Deployment, Artificial Intelligence and Machine Learning (AI/ML), CI/CD, Statistical Methods, Data Quality, Real Time Data, Resource Management
状态：免费试用您将获得的技能: Unsupervised Learning, Time Series Analysis and Forecasting, Supervised Learning, Machine Learning, Data Processing, Feature Engineering, Artificial Intelligence, Data Cleansing, Deep Learning, Statistical Analysis, Predictive Modeling, Classification And Regression Tree (CART), Regression Analysis
与 supervised learning 相关的搜索
总之，以下是 10 最受欢迎的 supervised learning 课程
- 监督式机器学习：回归与分类: DeepLearning.AI
- 使用 Python 进行机器学习: IBM
- Practical Machine Learning: Foundations to Neural Networks: Dartmouth College
- Machine Learning Fundamentals: Dartmouth College
- 机器学习: DeepLearning.AI
- 机器学习入门：监督学习: University of Colorado Boulder
- Supervised Learning Regression Classification Clustering: Simplilearn
- 机器学习数学: Imperial College London
- Applied Machine Learning: Johns Hopkins University
- 无监督学习、推荐器、强化学习: DeepLearning.AI
