MLOps (Machine Learning Operations)
最受欢迎
状态：免费试用DeepLearning.AI
状态：免费试用Duke University
状态：预览NVIDIA
状态：免费试用Google Cloud
当前趋势
状态：免费试用DeepLearning.AI
状态：免费试用Microsoft
状态：免费试用Google Cloud
状态：免费试用
最新发布
状态：免费试用Edureka
状态：免费试用Google Cloud
Pearson
状态：免费试用Pearson
筛选依据
主题必需的
语言必需的
在整个课程（说明和评估）中使用的语言。
了解产品必需的
级别必需的
课程长度必需的
字幕必需的
教师必需的
“mlops (machine learning operations)” 的结果
状态：免费试用Duke University
您将获得的技能: 集装箱化, 探索性数据分析, 数据分析, 数据操作, 应用程序部署, CI/CD, NumPy, 机器学习, MLOps（机器学习 Operator）, AWS SageMaker, 微软 Azure, Python 程序设计, 大数据, 负责任的人工智能, 数据管理, 云计算, 数据管道, Devops, GitHub, Pandas（Python 软件包）
状态：新您将获得的技能: MLOps (Machine Learning Operations), AWS SageMaker, CI/CD, DevOps, Data Processing, Data Management, Machine Learning, Predictive Modeling, Automation, Data Pipelines, Applied Machine Learning, Continuous Monitoring
状态：免费试用Google Cloud
您将获得的技能: Natural Language Processing, MLOps (Machine Learning Operations), Tensorflow, Large Language Modeling, Reinforcement Learning, Computer Vision, Google Cloud Platform, Keras (Neural Network Library), Systems Design, Image Analysis, AI Personalization, Hybrid Cloud Computing, Applied Machine Learning, Systems Architecture, Performance Tuning, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Machine Learning, Machine Learning Algorithms
- 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：新状态：免费试用您将获得的技能: MLOps (Machine Learning Operations), AWS SageMaker, Artificial Intelligence and Machine Learning (AI/ML), Amazon Web Services, Predictive Modeling, Applied Machine Learning, Data Processing, Regression Analysis, Machine Learning, Supervised Learning, Feature Engineering, Data Cleansing, Continuous Deployment, Unsupervised Learning
状态：新状态：免费试用您将获得的技能: AWS SageMaker, MLOps (Machine Learning Operations), Feature Engineering, AI Personalization, Amazon Web Services, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Amazon Elastic Compute Cloud, Data Cleansing, Data Processing, Data Wrangling, Data Integrity, Machine Learning, Machine Learning Algorithms, Data Modeling, Supervised Learning, Data Mining, Random Forest Algorithm, Data Management, Unsupervised Learning
是什么让您今天来到 Coursera？
状态：免费试用您将获得的技能: MLOps (Machine Learning Operations), Google Cloud Platform, Cloud Management, DevOps, Continuous Deployment, CI/CD, Machine Learning, Automation, Data Pipelines, Version Control
- 状态：预览
您将获得的技能: MLOps (Machine Learning Operations), Google Cloud Platform, DevOps, Application Lifecycle Management, Applied Machine Learning, Continuous Deployment, Machine Learning, Automation, Continuous Integration, Containerization, Data Processing
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
DeepLearning.AI
您将获得的技能: 应用程序部署, 持续部署, 机器学习, MLOps（机器学习 Operator）, 数据驱动的决策制定, 软件开发生命周期, 功能工程, 数据质量, 持续监测, 应用机器学习, 数据验证, 数据管道
状态：预览您将获得的技能: MLOps (Machine Learning Operations), Data Modeling, Google Cloud Platform, Feature Engineering, Application Deployment, DevOps, Data Processing, Data Management, Data Storage
状态：免费试用Google Cloud
您将获得的技能: MLOps (Machine Learning Operations), Google Cloud Platform, Data Management, Data Governance, Workflow Management, Tensorflow, Applied Machine Learning, Data Pipelines, Machine Learning, Cloud Computing, Data Transformation, Continuous Monitoring
