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  • Mlops

MLOps 课程

MLOps 课程可以帮助您学习机器学习项目的部署策略、模型监控以及持续集成和交付。您可以掌握自动化工作流、管理数据管道和确保符合治理标准的技能。许多课程介绍了 TensorFlow、Kubernetes 和 MLflow 等工具,这些工具支持操作 AI Model 并简化数据科学家和 IT 团队之间的协作。


热门 MLOps 课程和认证


  • P

    Packt

    AI Engineer Professional

    您将获得的技能: MLOps (Machine Learning Operations), Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Containerization, AI Workflows, Model Evaluation, Model Deployment, Generative AI Agents, LangGraph, Keras (Neural Network Library), Transfer Learning, Artificial Intelligence and Machine Learning (AI/ML), CrewAI, BeeAI, Image Analysis, Deep Learning, Large Language Modeling, Natural Language Processing, Vision Transformer (ViT), Python Programming

    高级设置 · 专项课程 · 1-3 个月

  • K

    KodeKloud

    ML Model Development and Tracking: Hands-on Guide

    您将获得的技能: MLOps (Machine Learning Operations), Model Deployment, Test Data, Model Evaluation, Data Synthesis, Development Environment, Claims Processing, Performance Tuning, Applied Machine Learning, Computer Hardware

    初级 · 课程 · 1-4 周

  • C

    Coursera

    AI Model Development & Deployment

    您将获得的技能: Model Deployment, AWS SageMaker, Software Documentation, Data Pipelines, MLOps (Machine Learning Operations), Tensorflow, Model Evaluation, Apache Airflow, Systems Design, Cloud Computing Architecture, Transfer Learning, Unit Testing, PyTorch (Machine Learning Library), API Design, Cloud Computing, Network Architecture, Deep Learning, Continuous Deployment, Python Programming, Data Validation

    中级 · 专项课程 · 1-3 个月

  • M

    Microsoft

    Microsoft Generative AI Engineering

    您将获得的技能: Generative AI, Responsible AI, Generative Model Architectures, Prompt Engineering, Multimodal Prompts, MLOps (Machine Learning Operations), Generative Adversarial Networks (GANs), Data Ethics, AI Orchestration, AI Workflows, Model Deployment, Azure DevOps, Microsoft Azure, ChatGPT, AI Security, AI Enablement, Model Evaluation, CI/CD, Artificial Intelligence and Machine Learning (AI/ML), Python Programming

    4.6
    评分, 4.6 星,最高 5 星
    ·
    8 条评论

    中级 · 专业证书 · 3-6 个月

  • W

    Whizlabs

    Fundamentals of Machine Learning

    您将获得的技能: Supervised Learning, Unsupervised Learning, MLOps (Machine Learning Operations), Applied Machine Learning, Model Evaluation, AWS SageMaker, Data Preprocessing, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Cloud Computing, Azure DevOps, Model Deployment, Microsoft Azure, Amazon Web Services, Deep Learning, Data Processing

    中级 · 课程 · 1-3 个月

  • C

    Coursera

    Automate, Optimize, and Monitor ML Models

    您将获得的技能: Verification And Validation, Data Pipelines

    中级 · 课程 · 1-4 周

  • C

    Coursera

    Deploying and Maintaining Production AI Systems

    您将获得的技能: Model Deployment, MLOps (Machine Learning Operations), Generative AI, Dependency Analysis, Dashboard, Application Deployment, Continuous Deployment, System Monitoring, Responsible AI, Performance Tuning, Site Reliability Engineering, Release Management, Kubernetes, Application Performance Management, CI/CD, Performance Analysis, Continuous Monitoring, Automation, Cloud Platforms, Data-Driven Decision-Making

    中级 · 课程 · 3-6 个月

  • C

    Coursera

    Testing and Refining LLM Applications

    您将获得的技能: MLOps (Machine Learning Operations), LLM Application, AI Security, Test Automation, Test Driven Development (TDD), Code Coverage, Unit Testing, CI/CD, Continuous Integration, Testability, Large Language Modeling, Model Deployment, Responsible AI, Maintainability, AI Workflows, Scripting, Software Engineering, Python Programming, Statistical Analysis, SQL

    中级 · 课程 · 1-3 个月

  • W

    Whizlabs

    Exam Prep MLA-C01: AWS Machine Learning Engineer Associate

    您将获得的技能: MLOps (Machine Learning Operations), Feature Engineering, AWS Kinesis, Fraud detection, Amazon Web Services, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Cloud Deployment, 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

    3.9
    评分, 3.9 星,最高 5 星
    ·
    10 条评论

    中级 · 专项课程 · 3-6 个月

  • P

    Pragmatic AI Labs

    Machine Learning with Databricks and MLflow

    您将获得的技能: MLOps (Machine Learning Operations), Databricks, Apache Spark, Model Evaluation, Hugging Face, Data Architecture, Recurrent Neural Networks (RNNs), LLM Application, Data Science, Data Mining, Mathematical Modeling, Scala Programming, Continuous Monitoring, Rust (Programming Language), Lean Six Sigma, Statistical Inference, Artificial Intelligence, Functional Testing, Exploratory Data Analysis, Programming Principles

    中级 · 课程 · 1-4 周

  • C

    Coursera

    Deploy & Optimize ML Services Confidently

    您将获得的技能: MLOps (Machine Learning Operations), Continuous Integration, Artificial Intelligence and Machine Learning (AI/ML), DevOps, Service Level Agreement, API Design, Performance Measurement, Performance Analysis

    中级 · 课程 · 1-4 周

  • C

    Coursera

    Advancing Your Career in Production AI

    您将获得的技能: Responsible AI, Data Ethics, Model Deployment, AI Product Strategy, Technical Design, Prompt Engineering, AI Security, Artificial Intelligence and Machine Learning (AI/ML), Model Evaluation, Technical Communication, Communication, AI Workflows, MLOps (Machine Learning Operations), LLM Application, Apache Airflow, System Design and Implementation, Python Programming, CI/CD, SQL, AWS CloudFormation

    中级 · 课程 · 1-4 周

与 mlops 相关的搜索

mlops | machine learning operations
mlops specialization
mlops (machine learning operations)
mlops platforms: amazon sagemaker and azure ml
mlops aws
mlops | machine learning operations specialization
mlops tools: mlflow and hugging face
mlops azure
1…456…35

总之,以下是 10 最受欢迎的 mlops 课程

  • AI Engineer Professional: Packt
  • ML Model Development and Tracking: Hands-on Guide: KodeKloud
  • AI Model Development & Deployment: Coursera
  • Microsoft Generative AI Engineering: Microsoft
  • Fundamentals of Machine Learning: Whizlabs
  • Automate, Optimize, and Monitor ML Models: Coursera
  • Deploying and Maintaining Production AI Systems: Coursera
  • Testing and Refining LLM Applications: Coursera
  • Exam Prep MLA-C01: AWS Machine Learning Engineer Associate: Whizlabs
  • Machine Learning with Databricks and MLflow: Pragmatic AI Labs

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