个结果，搜索词为 "machine learning 方法"
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DeepLearning.AI
您将获得的技能: 描述性统计, 机器学习, A/B 测试, 贝叶斯统计, 统计分析, 线性代数, 概率分布, 微积分, 统计推理, 数据转换, 数学建模, 概率与统计, 统计假设检验, NumPy, 概率, 应用数学, 降维, 抽样（统计）, Machine Learning 方法, 数值分析
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：新状态：免费试用您将获得的技能: Regression Analysis, Matplotlib, Feature Engineering, Time Series Analysis and Forecasting, Jupyter, Image Analysis, Scikit Learn (Machine Learning Library), Applied Machine Learning, Tensorflow, Data Visualization, Machine Learning Algorithms, Amazon Web Services, Python Programming, Cloud Applications, Data Transformation, Predictive Modeling, Data Processing, Health Informatics, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML)
状态：免费试用IBM
您将获得的技能: Python 程序设计, 机器学习, 预测建模, 深度学习, 机器学习算法, 探索性数据分析, 统计推理, 数据科学, 数据分析, 时间序列分析和预测, 强化学习, 回归分析, 数据访问, 生成模型架构, 降维, 数据清理, 功能工程, 应用机器学习, 监督学习, 无监督学习
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
是什么让您今天来到 Coursera？
状态：新状态：免费试用您将获得的技能: Responsible AI, Exploratory Data Analysis, Data Storytelling, Dashboard, Data Presentation, Data Literacy, No-Code Development, Business Analytics, Data Science, Applied Machine Learning, Data Capture, Data Modeling, Data Processing, Data Transformation, Data Ethics, MLOps (Machine Learning Operations), Machine Learning, Data Analysis, Predictive Modeling, Data Visualization
状态：免费试用University of Washington
您将获得的技能: 机器学习, 贝叶斯统计, 机器学习算法, 深度学习, 预测建模, 回归分析, 文本挖掘, 人工智能, 分类与回归树 (CART), 功能工程, 预测分析, 计算机视觉, 大数据, 应用机器学习, 无监督学习, 统计机器学习, 图像分析, 数据挖掘, 统计建模, 监督学习
状态：免费试用状态：人工智能技能University of Pennsylvania
您将获得的技能: Statistical Machine Learning, PyTorch (Machine Learning Library), Statistical Methods, Probability, Probability & Statistics, Sampling (Statistics), Deep Learning, Probability Distribution, Python Programming, Supervised Learning, Statistics, Machine Learning Methods, Machine Learning, Regression Analysis, Data Processing, Agentic systems, Data Science, Artificial Intelligence, Artificial Neural Networks, Algorithms
状态：新状态：免费试用您将获得的技能: Sampling (Statistics), Data Mining, Statistical Hypothesis Testing, Probability, Linear Algebra, Statistical Analysis, Statistical Inference, Data Analysis, Probability Distribution, Statistics, Machine Learning Algorithms, Machine Learning, Python Programming
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：免费试用您将获得的技能: Machine Learning Methods, Healthcare Ethics, Health Informatics, Machine Learning, Deep Learning, Clinical Informatics, Statistical Machine Learning, Predictive Modeling, Electronic Medical Record System, Machine Learning Algorithms, Data Mining, Data Processing, Data Analysis
总之，以下是 10 最受欢迎的 machine learning 方法 课程
- 机器学习: DeepLearning.AI
- 机器学习和数据科学数学: DeepLearning.AI
- Machine Learning Fundamentals: Dartmouth College
- AI Driven Machine Learning with Python: EDUCBA
- IBM 机器学习: IBM
- 机器学习数学: Imperial College London
- No-Code Machine Learning and Data Science for Everyone: LearnQuest
- 机器学习: University of Washington
- AI and Machine Learning Essentials with Python: University of Pennsylvania
- Machine Learning with Python & Statistics: EDUCBA
