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“machine learning methods” 的结果
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：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：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
状态：新状态：免费试用您将获得的技能: Data Processing
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
是什么让您今天来到 Coursera？
状态：免费试用Johns Hopkins University
您将获得的技能: Unsupervised Learning, Applied Machine Learning, Dimensionality Reduction, Reinforcement Learning, Regression Analysis, Machine Learning, Data Mining, Machine Learning Algorithms, Statistical Machine Learning, Advanced Analytics, Predictive Modeling, Random Forest Algorithm, Decision Tree Learning, Supervised Learning
状态：免费试用您将获得的技能: 机器学习, 预测建模, 分类与回归树 (CART), 监督学习, 回归分析, 无监督学习, 统计建模, 降维, 决策树学习, 应用机器学习, 功能工程, Scikit-learn （机器学习库）
状态：免费Amazon Web Services
您将获得的技能: Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Deep Learning, Artificial Intelligence, Amazon Web Services, Applied Machine Learning, Machine Learning
状态：免费试用Google Cloud
您将获得的技能: Feature Engineering, Prompt Engineering, Google Cloud Platform, Generative AI, Tensorflow, Keras (Neural Network Library), MLOps (Machine Learning Operations), Cloud Infrastructure, Data Pipelines, Cloud Platforms, Data Management, Data Governance, Workflow Management, Artificial Intelligence, Deep Learning, Applied Machine Learning, Machine Learning, Cloud Computing, Data Processing, Artificial Neural Networks
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
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
与 machine learning methods 相关的搜索
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
- Machine Learning with PyTorch and Scikit-Learn: Packt
- Foundations of Machine Learning: Coursera
- Advanced Machine Learning Techniques: Coursera
- The Nuts and Bolts of Machine Learning: Google
- Advanced Methods in Machine Learning Applications: Johns Hopkins University
- 使用 Python 进行机器学习: IBM
- Fundamentals of Machine Learning and Artificial Intelligence: Amazon Web Services
- Machine Learning on Google Cloud: Google Cloud
