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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：免费试用多位教师
您将获得的技能: 数据伦理, 机器学习, 分类与回归树 (CART), 人工智能, 预测建模, 人工智能和机器学习（AI/ML）, 无监督学习, NumPy, Python 程序设计, 强化学习, 随机森林算法, 应用机器学习, 决策树学习, 负责任的人工智能, Jupyter, 功能工程, 监督学习, 深度学习, 张力流, Scikit-learn （机器学习库）
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：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
状态：免费试用Imperial College London
您将获得的技能: Algorithm, 应用数学, 微积分, 机器学习, 线性代数, 数据科学, 数据操作, 回归分析, 衍生产品, Python 程序设计, 机器学习算法, 统计, NumPy, 降维, 人工神经网络, 概率与统计, Jupyter, 统计分析, 高等数学
是什么让您今天来到 Coursera？
状态：免费试用University of Washington
您将获得的技能: 机器学习, 人工智能, 预测建模, 计算机视觉, 分类与回归树 (CART), 监督学习, 文本挖掘, 回归分析, 统计建模, 无监督学习, 机器学习算法, 大数据, 功能工程, 统计机器学习, 应用机器学习, 数据挖掘, 图像分析, 贝叶斯统计, 深度学习, 预测分析
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, 数据科学, 预测建模, 数据分析, 统计推理, 无监督学习, 回归分析, 强化学习, 降维, 统计方法, 功能工程, Python 程序设计, 统计假设检验, 生成模型架构, 数据处理, 应用机器学习, 机器学习算法, 监督学习, 深度学习
状态：免费试用DeepLearning.AI
您将获得的技能: 应用数学, 机器学习, 线性代数, A/B 测试, 微积分, Machine Learning 方法, 数据转换, 统计推理, 抽样（统计）, NumPy, 降维, 概率, 概率分布, 描述性统计, 统计假设检验, 概率与统计, 数值分析, 统计分析, 贝叶斯统计, 数学建模
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Johns Hopkins University
您将获得的技能: PyTorch (Machine Learning Library), Unsupervised Learning, Computer Vision, Machine Learning Algorithms, Applied Machine Learning, Image Analysis, Dimensionality Reduction, Supervised Learning, Reinforcement Learning, Feature Engineering, Regression Analysis, Data Cleansing, Machine Learning, Data Mining, Scikit Learn (Machine Learning Library), Statistical Machine Learning, Advanced Analytics, Deep Learning, Artificial Neural Networks, Decision Tree Learning
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
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
- 机器学习: DeepLearning.AI
- Machine Learning with PyTorch and Scikit-Learn: Packt
- AWS Certified Machine Learning - Specialty: Pearson
- Foundations of Machine Learning: Coursera
- 机器学习数学: Imperial College London
- 机器学习: University of Washington
- IBM 机器学习: IBM
- 机器学习和数据科学数学: DeepLearning.AI
- AI and Machine Learning Essentials with Python: University of Pennsylvania
