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“machine learning 方法” 的结果
状态：新状态：免费试用您将获得的技能: Generative AI, Supervised Learning, Generative Model Architectures, Unsupervised Learning, Large Language Modeling, Time Series Analysis and Forecasting, Exploratory Data Analysis, LLM Application, Applied Machine Learning, Data Collection, Machine Learning Algorithms, OpenAI, Feature Engineering, Data Ethics, Dimensionality Reduction, MLOps (Machine Learning Operations), Machine Learning, Multimodal Prompts, Data Processing, Network Architecture
状态：新您将获得的技能: Exploratory Data Analysis, Data Analysis, Amazon Elastic Compute Cloud, Amazon CloudWatch, Application Deployment, Predictive Modeling, Data Pipelines, Data Processing
状态：免费试用多位教师
您将获得的技能: 机器学习, 数据伦理, 监督学习, 分类与回归树 (CART), 无监督学习, 人工智能, 决策树学习, 张力流, 负责任的人工智能, NumPy, 强化学习, 随机森林算法, Python 程序设计, 预测建模, 应用机器学习, Jupyter, 功能工程, 人工智能和机器学习（AI/ML）, Scikit-learn （机器学习库）, 深度学习
状态：免费试用IBM
您将获得的技能: 机器学习, 探索性数据分析, 统计方法, 数据分析, 回归分析, 监督学习, 无监督学习, 统计推理, 机器学习算法, 降维, 强化学习, 预测建模, 功能工程, 生成模型架构, 数据科学, Python 程序设计, 数据处理, 应用机器学习, 统计假设检验, 深度学习
状态：新状态：预览您将获得的技能: Reinforcement Learning, Dimensionality Reduction, PyTorch (Machine Learning Library), Deep Learning, Generative AI, Pandas (Python Package), Scikit Learn (Machine Learning Library), Python Programming, Machine Learning, Artificial Neural Networks, Data Processing, Natural Language Processing, Feature Engineering, Predictive Modeling, Supervised Learning, Unsupervised Learning, Data Transformation, NumPy
状态：新状态：免费试用Coursera
您将获得的技能: Supervised Learning, Unsupervised Learning, Time Series Analysis and Forecasting, Applied Machine Learning, Machine Learning Algorithms, Feature Engineering, Dimensionality Reduction, Machine Learning, Predictive Modeling, Predictive Analytics, Scikit Learn (Machine Learning Library), Forecasting, Data Processing, Anomaly Detection, Data Manipulation, Regression Analysis, Statistical Modeling, Data Transformation, Data Cleansing
是什么让您今天来到 Coursera？
状态：免费试用DeepLearning.AI
您将获得的技能: 线性代数, 概率与统计, 机器学习, A/B 测试, Machine Learning 方法, 数学建模, 数值分析, 数据转换, 统计推理, 抽样（统计）, NumPy, 贝叶斯统计, 概率, 降维, 应用数学, 微积分, 统计假设检验, 描述性统计, 概率分布, 统计分析
状态：免费试用Imperial College London
您将获得的技能: 概率与统计, 线性代数, 机器学习, 回归分析, Algorithm, 数据操作, 降维, Python 程序设计, NumPy, 人工神经网络, 统计, 机器学习算法, 微积分, 应用数学, Jupyter, 衍生产品, 高等数学, 数据科学, 统计分析
状态：免费试用您将获得的技能: Feature Engineering, Applied Machine Learning, Advanced Analytics, Machine Learning, Unsupervised Learning, Workflow Management, Data Ethics, Supervised Learning, Data Validation, Classification And Regression Tree (CART), Random Forest Algorithm, Decision Tree Learning, Python Programming, Performance Tuning
状态：免费试用您将获得的技能: 机器学习, 回归分析, 决策树学习, 分类与回归树 (CART), 无监督学习, 监督学习, 统计建模, 降维, 预测建模, 应用机器学习, 功能工程, Scikit-learn （机器学习库）
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：免费试用Microsoft
您将获得的技能: 机器学习, 回归分析, 无监督学习, 监督学习, 人工智能, 人工智能和机器学习（AI/ML）, 机器学习算法, 应用机器学习, 预测建模, 微软 Azure, 自动化, 无代码开发
总之，以下是 10 最受欢迎的 machine learning 方法 课程
- Machine Learning with Scikit-learn, PyTorch & Hugging Face: Coursera
- AWS Certified Machine Learning - Specialty: Pearson
- 机器学习: DeepLearning.AI
- IBM 机器学习: IBM
- Machine Learning with PyTorch and Scikit-Learn: Packt
- Foundations of Machine Learning: Coursera
- 机器学习和数据科学数学: DeepLearning.AI
- 机器学习数学: Imperial College London
- The Nuts and Bolts of Machine Learning: Google
- 使用 Python 进行机器学习: IBM
