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  • Ml Explainability

Results for "ml explainability"


  • Status: New
    New
    Status: Free Trial
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    C

    Coursera

    Debug ML Code: Fix, Trace & Evaluate

    Skills you'll gain: Regression Testing, Debugging, Unit Testing, Test Case, Code Review, Root Cause Analysis, Software Documentation

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
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    Coursera

    ML: Build, Train, Justify Models

    Skills you'll gain: Model Training, Predictive Modeling, Applied Machine Learning, Machine Learning Methods, Statistical Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Statistical Modeling, Technical Communication

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    Duke University

    Developing Explainable AI (XAI)

    Skills you'll gain: Responsible AI, Data Ethics, Generative AI, Artificial Intelligence, AI literacy, Decision Intelligence, Machine Learning, Machine Learning Methods, Model Evaluation, Artificial Neural Networks, Information Privacy

    4.6
    Rating, 4.6 out of 5 stars
    ·
    59 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Coursera

    Evaluate and Create ML Workflows Visually

    Skills you'll gain: Model Training, MLOps (Machine Learning Operations), Software Visualization, Grafana, Code Reusability, Performance Metric, Data Pipelines, Performance Analysis, Collaborative Software

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Coursera

    Optimize ML Dev: Version, Reproduce, and Save

    Skills you'll gain: Git (Version Control System), Model Training, Version Control, AI Workflows, Jupyter, Memory Management, Package and Software Management, Resource Utilization, Virtual Environment

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Coursera

    Integrate, Scale, and Monitor ML Microservices

    Skills you'll gain: Microservices, MLOps (Machine Learning Operations), Application Performance Management, AI Integrations, Site Reliability Engineering, AI Workflows, Continuous Monitoring, Performance Analysis, Event-Driven Programming

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Coursera

    Develop Production-Ready ML APIs with MLOps

    Skills you'll gain: MLOps (Machine Learning Operations), AI Workflows, API Design, CI/CD, Software Quality Assurance, Code Review, Software Engineering, Software Versioning

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
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    Coursera

    Deploy & Optimize ML Services Confidently

    Skills you'll gain: MLOps (Machine Learning Operations), Continuous Integration, Artificial Intelligence and Machine Learning (AI/ML), Service Level Agreement, Performance Stress Testing, Performance Measurement, Performance Analysis

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Coursera

    Automate and Evaluate ML Pipeline Tests

    Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Regression Testing, Unit Testing, Test Script Development, Test Case, System Testing, Test Automation, Software Testing, Integration Testing, Verification And Validation, Anomaly Detection, Data Integrity, Continuous Monitoring

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Coursera

    Validate, Analyze, and Monitor ML Models

    Skills you'll gain: Verification And Validation, Release Management, Maintainability, Experimentation, Performance Testing, Benchmarking, Performance Analysis

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
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    Coursera

    Engineer, Validate, and Govern ML Data

    Skills you'll gain: Apache Airflow, Data Governance, Data Management, Apache Spark, PySpark, Databricks, Record Keeping

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    Duke University

    DevOps, DataOps, MLOps

    Skills you'll gain: MLOps (Machine Learning Operations), GitHub Copilot, Responsible AI, Model Deployment, Containerization, Web Frameworks, Rust (Programming Language), AI Workflows, DevOps, Hugging Face, Applied Machine Learning, Cloud Solutions, Cloud-Native Computing, Machine Learning, Serverless Computing, Application Deployment, GitHub, Command-Line Interface, Big Data

    4.1
    Rating, 4.1 out of 5 stars
    ·
    221 reviews

    Advanced · Course · 1 - 3 Months

1234…117

In summary, here are 10 of our most popular ml explainability courses

  • Debug ML Code: Fix, Trace & Evaluate: Coursera
  • ML: Build, Train, Justify Models: Coursera
  • Developing Explainable AI (XAI): Duke University
  • Evaluate and Create ML Workflows Visually: Coursera
  • Optimize ML Dev: Version, Reproduce, and Save: Coursera
  • Integrate, Scale, and Monitor ML Microservices: Coursera
  • Develop Production-Ready ML APIs with MLOps: Coursera
  • Deploy & Optimize ML Services Confidently: Coursera
  • Automate and Evaluate ML Pipeline Tests: Coursera
  • Validate, Analyze, and Monitor ML Models: Coursera

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