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, 预测建模, 机器学习, 逻辑回归, Scikit-learn （机器学习库）, 监督学习, 模型评估, NumPy, 分类算法, Python 程序设计, 人工智能, 无监督学习, Jupyter, 数据预处理, 功能工程
状态：免费试用您将获得的技能: 回归分析, 模型评估, Scikit-learn （机器学习库）, 预测建模, 降维, 机器学习, 逻辑回归, 监督学习, Python 程序设计, 分类算法, 无监督学习, 功能工程, 决策树学习, 应用机器学习
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：免费试用多位教师
您将获得的技能: 模型评估, 迁移学习, 机器学习, 预测建模, NumPy, Scikit-learn （机器学习库）, 监督学习, 强化学习, 分类算法, 人工智能, Jupyter, 决策树学习, 无监督学习, 张力流, 随机森林算法, 数据伦理, 深度学习, 数据预处理, 应用机器学习, 功能工程
状态：免费试用Imperial College London
您将获得的技能: 回归分析, 降维, 微积分, 应用数学, NumPy, 人工神经网络, Python 程序设计, 衍生产品, 功能工程, Algorithm, 高等数学, 统计, 数学建模, 机器学习算法, 数据预处理, 无监督学习, Jupyter, 线性代数
状态：免费试用Alberta Machine Intelligence Institute
您将获得的技能: 回归分析, 机器学习, 模型评估, Scikit-learn （机器学习库）, 监督学习, 性能分析, Python 程序设计, 业务解决方案, 分类算法, 功能工程, 决策树学习, 数据处理, 机器学习算法, 数据预处理, 应用机器学习, 工艺优化, Jupyter
是什么让您今天来到 Coursera？
状态：免费试用University of Michigan
您将获得的技能: Unsupervised Learning, Embeddings, Supervised Learning, Data Preprocessing, Python Programming, Exploratory Data Analysis
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
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
状态：免费试用IBM
您将获得的技能: 概率与统计, 统计分析, 探索性数据分析, 数据访问, 数据导入/导出, 数据操作, 机器学习, 统计假设检验, 统计方法, 异常检测, 统计推理, Pandas（Python 软件包）, Jupyter, 数据分析, 数据清理, 数据预处理, 数据质量, 功能工程, 数据转换
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 Fundamentals: Dartmouth College
- 机器学习: DeepLearning.AI
- 机器学习数学: Imperial College London
- 机器学习算法：监督学习从头到尾: Alberta Machine Intelligence Institute
- Applied Unsupervised Learning in Python: University of Michigan
- Supervised Learning Regression Classification Clustering: Simplilearn
- Applied Machine Learning: Johns Hopkins University
- NVIDIA: Fundamentals of Machine Learning: Whizlabs
