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    MLOps

    833 курсов
    Metaflow
    Introduction to MLOps: What, Why, and How
    NashKnolX

    Introduction to MLOps: What, Why, and How

    Build and Deploy Machine Learning Models on Azure ML Studio
    NashKnolX

    Build and Deploy Machine Learning Models on Azure ML Studio

    An Overview of MLOps Pipeline: Automating ML Workflow with Azure Cloud
    NashKnolX

    An Overview of MLOps Pipeline: Automating ML Workflow with Azure Cloud

    Why ML in Production is Still Broken
    Toronto Machine Learning Series (TMLS)

    Why ML in Production is Still Broken

    Simplify ML Pipeline Automation and Tracking Using Kubeflow and Serverless Functions
    Toronto Machine Learning Series (TMLS)

    Simplify ML Pipeline Automation and Tracking Using Kubeflow and Serverless Functions

    Automated Pipeline for Large-Scale Neural Network Training and Inference
    Toronto Machine Learning Series (TMLS)

    Automated Pipeline for Large-Scale Neural Network Training and Inference

    MLOps at Scale: Predicting Bus Departure Times Using 18,000 ML Models
    Toronto Machine Learning Series (TMLS)

    MLOps at Scale: Predicting Bus Departure Times Using 18,000 ML Models

    MLOps and Automation Workshop - Bringing Machine Learning to Production in a Few Easy Steps
    Toronto Machine Learning Series (TMLS)

    MLOps and Automation Workshop - Bringing Machine Learning to Production in a Few Easy Steps

    Serverless for Machine Learning Pipelines
    Toronto Machine Learning Series (TMLS)

    Serverless for Machine Learning Pipelines

    Principles of Good Machine Learning Systems Design
    Toronto Machine Learning Series (TMLS)

    Principles of Good Machine Learning Systems Design

    Simplifying Machine Learning Lifecycle Management in Healthcare
    Toronto Machine Learning Series (TMLS)

    Simplifying Machine Learning Lifecycle Management in Healthcare

    MLOps Without Much Ops - Building Efficient Machine Learning Systems
    Toronto Machine Learning Series (TMLS)

    MLOps Without Much Ops - Building Efficient Machine Learning Systems

    AI and Advanced Analytics in Retail
    Toronto Machine Learning Series (TMLS)

    AI and Advanced Analytics in Retail

    Cloud Native Artificial Intelligence - Top to Bottom
    Linux Foundation

    Cloud Native Artificial Intelligence - Top to Bottom

    Scaling AI in Australia and New Zealand - ML Foundations and Databricks
    Databricks

    Scaling AI in Australia and New Zealand - ML Foundations and Databricks

    Reduce Spend and Turbocharge Databricks Performance with Cognizant and Partners
    Databricks

    Reduce Spend and Turbocharge Databricks Performance with Cognizant and Partners

    Lightning-fast R and Python Library Loading for Databricks Clusters
    Databricks

    Lightning-fast R and Python Library Loading for Databricks Clusters

    Simplifying Data Ingestion for LLMs with Unstructured and Databricks
    Databricks

    Simplifying Data Ingestion for LLMs with Unstructured and Databricks

    MLOps: Using Python Libraries in DotNet - Spacy, Numpy, Pandas
    The Machine Learning Engineer

    MLOps: Using Python Libraries in DotNet - Spacy, Numpy, Pandas

    MLOps: Comparing Microsoft Phi3 Mini 128k in GGUF, MLFlow, and ONNX Formats
    The Machine Learning Engineer

    MLOps: Comparing Microsoft Phi3 Mini 128k in GGUF, MLFlow, and ONNX Formats

    MLOps with MLFlow: Working with Spacy NLP and Training NER Models
    The Machine Learning Engineer

    MLOps with MLFlow: Working with Spacy NLP and Training NER Models