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
DeepLearning.AI
您将获得的技能: 逻辑回归, 模型培训, 模型优化, 人工智能, 功能工程, 算法, Python 编程, 监督学习, 机器学习, Model Evaluation, Algorithm, 应用机器学习, Jupyter, 回归分析, 模型评估, 机器学习算法, 数据预处理, 预测建模, Scikit Learn（机器学习库）, 分类算法, NumPy
多位教师
您将获得的技能: 模型培训, 无监督学习, 人工智能, 决策树学习, 机器学习方法, 监督学习, 数据伦理, 张力流, 机器学习, Model Evaluation, 应用机器学习, Transfer Learning, 深度学习, Jupyter, Scikit Learn（机器学习库）, 机器学习算法, 模型评估, 迁移学习, 负责任的人工智能, 预测建模, 分类算法, NumPy
Coursera
您将获得的技能: Random Forest Algorithm, Model Evaluation, Feature Engineering, Model Training, Applied Machine Learning, Supervised Learning, Geospatial Mapping, Predictive Modeling, Image Analysis, Verification And Validation, Data Science, Environmental Engineering
Alberta Machine Intelligence Institute
您将获得的技能: 模型培训, 模型优化, 决策树学习, 机器学习方法, 监督学习, 性能分析, Python 编程, 机器学习, Model Evaluation, 回归分析, Jupyter, 业务解决方案, 应用机器学习, 数据预处理, 机器学习算法, 统计机器学习, 模型评估, 数据处理, 分类算法
您将获得的技能: 逻辑回归, 模型培训, 无监督学习, 模型优化, 降维, 决策树学习, 监督学习, 机器学习方法, Python 编程, 机器学习, Model Evaluation, 应用机器学习, 回归分析, 机器学习算法, 模型评估, Scikit Learn（机器学习库）, 预测建模, 统计机器学习, 预测分析, 分类算法
IBM
您将获得的技能: 逻辑回归, 模型培训, 模型优化, 决策树学习, 机器学习方法, 抽样（统计）, 业务逻辑, 监督学习, 机器学习, Model Evaluation, 应用机器学习, 回归分析, 数据预处理, Scikit Learn（机器学习库）, 统计机器学习, 机器学习算法, 模型评估, 预测建模, 随机森林算法, 数据清理, 分类算法
是什么让您今天来到 Coursera？
University of Colorado Boulder
您将获得的技能: Classification And Regression Tree (CART), Applied Machine Learning, Statistical Machine Learning, Machine Learning Methods, Model Training, Model Optimization
Johns Hopkins University
您将获得的技能: Computer Vision, Model Evaluation, PyTorch (Machine Learning Library), Supervised Learning, Unsupervised Learning, Image Analysis, Applied Machine Learning, Data Preprocessing, Dimensionality Reduction, Machine Learning Methods, Reinforcement Learning, Feature Engineering, Machine Learning Algorithms, Convolutional Neural Networks, Regression Analysis, Data Processing, Model Training, Machine Learning, Deep Learning, Model Optimization
Dartmouth College
您将获得的技能: Supervised Learning, Predictive Modeling, Logistic Regression, Statistical Modeling, Model Evaluation, Statistical Machine Learning, Machine Learning Methods, Applied Machine Learning, Machine Learning, Generative Model Architectures, Machine Learning Algorithms, Classification Algorithms, Model Optimization, Regression Analysis, Probability & Statistics
IBM
您将获得的技能: 无监督学习, 降维, 数据科学, 数据分析, 数据挖掘, 机器学习, Model Evaluation, 大数据, 应用机器学习, 数据预处理, Scikit Learn（机器学习库）, 机器学习算法, 模型评估, 文本挖掘
您将获得的技能: Data Preprocessing, Unsupervised Learning, Model Evaluation, Time Series Analysis and Forecasting, Supervised Learning, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Algorithms, Model Training, Feature Engineering, Artificial Intelligence, Deep Learning, Classification Algorithms, Generative AI, Model Optimization, Regression Analysis
您将获得的技能: Machine Learning Methods, Healthcare Ethics, Health Informatics, Machine Learning, Deep Learning, Statistical Machine Learning, Model Training, Convolutional Neural Networks, Data Preprocessing, Predictive Modeling, Electronic Medical Record System, AI Personalization, Machine Learning Algorithms, Recurrent Neural Networks (RNNs), Model Evaluation, Decision Intelligence, Data Analysis
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
- 机器学习: DeepLearning.AI
- Train ML Models: Coursera
- 机器学习算法：监督学习从头到尾: Alberta Machine Intelligence Institute
- 使用 Python 进行机器学习: IBM
- 有监督的机器学习：分类: IBM
- Introduction to Machine Learning: Supervised Learning: University of Colorado Boulder
- Applied Machine Learning: Johns Hopkins University
- Machine Learning Fundamentals: Dartmouth College
- 无监督机器学习: IBM
