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: 回归分析, Model Evaluation, 人工智能, 数据预处理, 分类算法, 无监督学习, 预测建模, Jupyter, Scikit-learn （机器学习库）, 功能工程, 机器学习, 逻辑回归, 监督学习, NumPy, Python 程序设计
状态：免费试用您将获得的技能: 回归分析, Model Evaluation, 监督学习, 分类算法, 无监督学习, Scikit-learn （机器学习库）, 机器学习, 预测建模, 逻辑回归, 应用机器学习, 功能工程, 决策树学习, 降维, Python 程序设计
状态：新状态：免费试用您将获得的技能: Unsupervised Learning, Feature Engineering, Model Evaluation, Applied Machine Learning, Statistical Machine Learning, Predictive Modeling, Supervised Learning, Clinical Informatics, Machine Learning, Health Informatics, Data Preprocessing, Clinical Data Management, Predictive Analytics, Patient Safety, Decision Tree Learning, Time Series Analysis and Forecasting, Logistic Regression, Forecasting, Classification Algorithms, Dimensionality Reduction
状态：免费试用多位教师
您将获得的技能: Model Evaluation, 深度学习, 人工智能, 预测建模, Jupyter, 分类算法, Transfer Learning, 强化学习, 无监督学习, 数据伦理, 监督学习, 数据预处理, NumPy, 张力流, Scikit-learn （机器学习库）, 功能工程, 随机森林算法, 应用机器学习, 决策树学习, 机器学习
状态：免费试用Alberta Machine Intelligence Institute
您将获得的技能: 回归分析, Model Evaluation, 机器学习算法, 数据预处理, 监督学习, 业务解决方案, 分类算法, 工艺优化, 数据处理, 功能工程, Scikit-learn （机器学习库）, Jupyter, 决策树学习, 机器学习, Python 程序设计, 应用机器学习, 性能分析
状态：免费试用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, Reinforcement Learning, Feature Engineering, Machine Learning Algorithms, Convolutional Neural Networks, Regression Analysis, Data Processing, Machine Learning, Data Mining, Data Cleansing, Deep Learning, Artificial Neural Networks
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 Algorithms, Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Decision Tree Learning, Predictive Analytics, Logistic Regression, Random Forest Algorithm, Bayesian Statistics
状态：免费试用IBM
您将获得的技能: Model Evaluation, 数据清理, 数据预处理, 分类算法, 性能指标, 预测建模, 抽样（统计）, 逻辑回归, 功能工程, 随机森林算法, 决策树学习, 机器学习, Scikit-learn （机器学习库）, 监督学习
状态：免费试用您将获得的技能: Data Preprocessing, Unsupervised Learning, Model Evaluation, Time Series Analysis and Forecasting, Supervised Learning, Machine Learning, Feature Engineering, Artificial Intelligence, Deep Learning, Classification Algorithms, Statistical Analysis, Regression Analysis
状态：新状态：免费试用Dartmouth College
您将获得的技能: Supervised Learning, Predictive Modeling, Logistic Regression, Statistical Modeling, Model Evaluation, Machine Learning, Machine Learning Algorithms, Classification Algorithms, Regression Analysis, Probability & Statistics, Linear Algebra
状态：免费试用IBM
您将获得的技能: Algorithm, 机器学习算法, 文本挖掘, 数据预处理, 数据科学, 无监督学习, 数据分析, 功能工程, Scikit-learn （机器学习库）, 降维, 大数据, 机器学习
状态：新状态：免费试用您将获得的技能: Healthcare Ethics, Health Informatics, Machine Learning, Deep Learning, Machine Learning Software, Clinical Informatics, Statistical Machine Learning, Convolutional Neural Networks, Data Preprocessing, Predictive Modeling, Electronic Medical Record System, Machine Learning Algorithms, Recurrent Neural Networks (RNNs), Model Evaluation, Data 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
- Machine Learning for Healthcare Applications: SkillUp
- 机器学习: DeepLearning.AI
- 机器学习算法：监督学习从头到尾: Alberta Machine Intelligence Institute
- Applied Machine Learning: Johns Hopkins University
- Supervised Learning Regression Classification Clustering: Simplilearn
- 有监督的机器学习：分类: IBM
- NVIDIA: Fundamentals of Machine Learning: Whizlabs
- Machine Learning Fundamentals: Dartmouth College
