个结果，搜索词为 "machine learning methods"
状态：免费试用多位教师
您将获得的技能: 无监督学习, 机器学习, NumPy, 数据伦理, Scikit Learn（机器学习库）, 模型评估, 人工智能, 深度学习, 机器学习算法, 张力流, Model Evaluation, 决策树学习, 负责任的人工智能, 模型培训, 迁移学习, 分类算法, 监督学习, 应用机器学习, Jupyter, 机器学习方法, 预测建模, Transfer Learning
状态：免费试用DeepLearning.AI
您将获得的技能: 模型优化, 统计方法, 机器学习, 降维, 抽样（统计）, 数据转换, 概率, 统计推理, 概率与统计, 贝叶斯统计, 数学软件, 线性代数, 微积分, 统计资料, 概率分布, 应用机器学习, 统计假设检验, 描述性统计, 机器学习方法, 应用数学
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, Data Preprocessing, Model Evaluation, PyTorch (Machine Learning Library), Statistical Methods, Probability, Probability & Statistics, Sampling (Statistics), Logistic Regression, Deep Learning, Probability Distribution, Statistical Modeling, Python Programming, Supervised Learning, Machine Learning, Data Processing, Agentic systems, Artificial Intelligence, Algorithms, AI literacy
状态：免费试用Google Cloud
您将获得的技能: Feature Engineering, Model Optimization, Generative AI, Model Deployment, Tensorflow, Generative AI Agents, Google Gemini, Model Training, Keras (Neural Network Library), Machine Learning, Generative Model Architectures, Data Preprocessing, Machine Learning Software, Machine Learning Methods, MLOps (Machine Learning Operations), Google Cloud Platform, Model Evaluation, Data Cleansing, Data Quality, Cloud Computing
状态：免费试用Johns Hopkins University
您将获得的技能: Model Evaluation, Unsupervised Learning, Applied Machine Learning, Dimensionality Reduction, Reinforcement Learning, Machine Learning Methods, Regression Analysis, Machine Learning, Data Mining, Machine Learning Algorithms, Predictive Modeling, Random Forest Algorithm, Decision Tree Learning, Model Optimization, Logistic Regression, Classification Algorithms
状态：免费试用Imperial College London
您将获得的技能: 数据科学, 统计方法, 模型优化, 降维, 几何学, 无监督学习, 数据转换, NumPy, 数值分析, 数据操作, 数学软件, 线性代数, 回归分析, 人工神经网络, 微积分, 统计资料, Jupyter, 应用机器学习, 描述性统计, 应用数学
是什么让您今天来到 Coursera？
状态：新您将获得的技能: Model Evaluation, Classification Algorithms, R Programming, Apache Spark, Deep Learning, Applied Machine Learning, Data Wrangling, Keras (Neural Network Library), Unsupervised Learning, Model Training, Statistical Machine Learning, Data Manipulation, Machine Learning Methods, Machine Learning Algorithms, Data Science, Machine Learning, Tidyverse (R Package), Data Analysis, Bayesian Network, Logistic Regression
状态：免费试用您将获得的技能: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Model Training, Random Forest Algorithm, Model Optimization, Predictive Modeling, Model Evaluation, Python Programming, Performance Tuning, Classification Algorithms
状态：免费试用Johns Hopkins University
您将获得的技能: 数据预处理, 模型评估, 机器学习, 机器学习软件, 机器学习算法, Model Evaluation, 分类与回归树 (CART), 预测分析, R 程序设计, 模型培训, 回归分析, 应用机器学习, 分类算法, 功能工程, 监督学习, 预测建模, 随机森林算法, 机器学习方法
状态：免费试用Coursera
您将获得的技能: 数据预处理, 模型评估, 无监督学习, Scikit Learn（机器学习库）, 统计机器学习, 机器学习, 降维, 机器学习软件, 预测, Model Evaluation, 机器学习算法, 预测分析, 模型培训, 分类算法, 监督学习, 数据整理, 时间序列分析和预测, 功能工程, 应用机器学习, 预测建模, 机器学习方法
状态：免费试用您将获得的技能: Python 编程, 逻辑回归, 无监督学习, 降维, 模型评估, 机器学习, 统计机器学习, Scikit Learn（机器学习库）, 模型优化, 机器学习算法, Model Evaluation, 决策树学习, 预测分析, 模型培训, 回归分析, 监督学习, 应用机器学习, 分类算法, 机器学习方法, 预测建模
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, 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
总之，以下是 10 最受欢迎的 machine learning methods 课程
- 机器学习: DeepLearning.AI
- 机器学习和数据科学数学: DeepLearning.AI
- AI and Machine Learning Essentials with Python: University of Pennsylvania
- Machine Learning on Google Cloud: Google Cloud
- Advanced Methods in Machine Learning Applications: Johns Hopkins University
- Mathematics for Machine Learning: Imperial College London
- Machine Learning with R: Packt
- The Nuts and Bolts of Machine Learning: Google
- 实用机器学习: Johns Hopkins University
- 机器学习基础: Coursera
