Results for "ml 部署面临的挑战"
Status: Free TrialMicrosoft
Skills you'll gain: Unsupervised Learning, Generative AI, Large Language Modeling, Data Management, Natural Language Processing, MLOps (Machine Learning Operations), Supervised Learning, Microsoft Azure, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Infrastructure Architecture, LLM Application, Responsible AI, Generative AI Agents, Applied Machine Learning, Reinforcement Learning, Data Ethics, Prompt Engineering, Data Processing, Application Deployment
Status: Free TrialDuke University
Skills you'll gain: MLOps (Machine Learning Operations), Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Application Deployment, Responsible AI, Data Manipulation, Exploratory Data Analysis, Containerization, Data Pipelines, CI/CD, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis
Status: NewStatus: Free TrialSkills you'll gain: Feature Engineering, Microsoft Azure, Applied Machine Learning, Machine Learning, Machine Learning Algorithms, Data Processing, Data Cleansing, Supervised Learning, Data Transformation, MLOps (Machine Learning Operations), Application Deployment, Artificial Intelligence and Machine Learning (AI/ML), CI/CD, Statistical Methods, Data Quality, Real Time Data, Resource Management
Status: Free TrialSkills you'll gain: Supervised Learning, Data Modeling, Unsupervised Learning, Applied Machine Learning, Data Analysis, Reinforcement Learning, Artificial Intelligence, Classification And Regression Tree (CART), Tensorflow, Machine Learning Algorithms, Keras (Neural Network Library), Artificial Neural Networks, Deep Learning, Predictive Modeling, Machine Learning, Regression Analysis, Data Ethics, Responsible AI, Artificial Intelligence and Machine Learning (AI/ML), Random Forest Algorithm
Status: Free TrialSkills you'll gain: Business Transformation, Innovation, Digital Transformation, Serverless Computing, Cloud Services, Data Ethics, Cloud Infrastructure, Google Cloud Platform, Application Programming Interface (API), Technology Strategies, Applied Machine Learning, Hybrid Cloud Computing, Data Strategy, Image Analysis, Infrastructure As A Service (IaaS), Responsible AI, Cloud Computing, Cloud Solutions, Public Cloud, Containerization
Status: NewSkills you'll gain: Data Engineering, Application Deployment, YAML, Virtual Environment
What brings you to Coursera today?
Status: NewStatus: Free TrialSkills you'll gain: Statistical Methods
Status: NewGoogle Cloud
Skills you'll gain: Prompt Engineering, Generative AI Agents, Generative AI, AI Product Strategy, Tool Calling, Google Cloud Platform, Artificial Intelligence and Machine Learning (AI/ML), Organizational Strategy, Business Transformation, Innovation, Customer Engagement
Status: NewStatus: Free TrialSkills you'll gain: Feature Engineering, Microsoft Azure, Applied Machine Learning, Machine Learning, Machine Learning Algorithms, Data Processing, Data Cleansing, Supervised Learning, Data Transformation, MLOps (Machine Learning Operations), Application Deployment, Artificial Intelligence and Machine Learning (AI/ML), Data Quality, Resource Management
Status: Free TrialSkills you'll gain: Predictive Modeling, Responsible AI, Predictive Analytics, Machine Learning, Data Ethics, MLOps (Machine Learning Operations), Applied Machine Learning, Data-Driven Decision-Making, Statistical Modeling, Performance Measurement, Supervised Learning, Business Ethics, Decision Tree Learning, Artificial Intelligence and Machine Learning (AI/ML), Leadership and Management, Business Analytics, Data Science, Machine Learning Algorithms, Artificial Intelligence, Data Processing
Status: Free TrialSkills you'll gain: MLOps (Machine Learning Operations), Google Cloud Platform, Cloud Management, DevOps, Continuous Deployment, CI/CD, Machine Learning, Automation, Data Pipelines, Version Control
Status: Free TrialSkills you'll gain: Feature Engineering, Tensorflow, Google Cloud Platform, Data Quality, Data Cleansing, Scikit Learn (Machine Learning Library), Keras (Neural Network Library), Machine Learning, Exploratory Data Analysis, Applied Machine Learning, Supervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Responsible AI, Data Pipelines, PyTorch (Machine Learning Library), Jupyter, MLOps (Machine Learning Operations), Artificial Neural Networks, Machine Learning Methods, Data Transformation
In summary, here are 10 of our most popular ml 部署面临的挑战 courses
- Microsoft AI & ML Engineering: Microsoft
- MLOps | Machine Learning Operations: Duke University
- Azure ML Bootcamp: Machine Learning on the Cloud: Packt
- AI ML with Deep Learning and Supervised Models: Simplilearn
- Digital Transformation Using AI/ML with Google Cloud: Google Cloud
- DevOps to MLOps Bootcamp– Build & Deploy ML Systems: Packt
- Building, Evaluating, and Operationalizing ML Models: Packt
- 生成式 AI 智能体：助力组织转型: Google Cloud
- Foundations of Machine Learning with Azure: Packt
- Machine Learning Rock Star – the End-to-End Practice: SAS
