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  • Ml Explainability

Results for "ml explainability"


  • C

    Coursera

    Interpretable Machine Learning Applications: Part 2

    Skills you'll gain: Model Evaluation, Applied Machine Learning, Data Preprocessing, Classification Algorithms, Random Forest Algorithm, Data Transformation, Machine Learning Methods, Model Training, Predictive Modeling, Regression Analysis, Feature Engineering, Decision Tree Learning, Machine Learning, Exploratory Data Analysis, Performance Measurement

    ★ 4.3 (28) · Beginner · Guided Project · Less Than 2 Hours

    Category: Credit offered
    Credit offered
  • M

    Microsoft

    Microsoft Azure for AI and Machine Learning

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Microsoft Azure, Artificial Intelligence and Machine Learning (AI/ML), AI Integrations, Model Training, Cloud Deployment, Data Pipelines, AI Workflows, AI Security, Data Preprocessing, CI/CD, Continuous Monitoring, Identity and Access Management, Version Control, Data Storage

    ★ 4.6 (25) · Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Apply Test-Driven ML Code

    Skills you'll gain: Unit Testing, Test Driven Development (TDD), Continuous Integration, CI/CD, Software Testing, Continuous Deployment, Testability, Test Script Development, Model Training, MLOps (Machine Learning Operations), Tensorflow, Maintainability, Applied Machine Learning, Software Engineering, Code Reusability, Machine Learning Methods, Python Programming

    Intermediate · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google Cloud

    Machine Learning Operations (MLOps) with Vertex AI: Manage Features

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Data Modeling, Google Cloud Platform, Feature Engineering, Model Training, Data Store, Data Preprocessing, Data Processing, Data Management, Data Storage Technologies

    ★ 4.1 (16) · Intermediate · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Automate, Evaluate and Deploy ML Models Confidently

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Scalability, Model Optimization, CI/CD, Continuous Deployment, Machine Learning Software, Continuous Delivery, Model Training, DevOps, Artificial Intelligence and Machine Learning (AI/ML), Model Evaluation, Continuous Integration, Performance Measurement, Business Metrics, Automation, Business Priorities, Performance Analysis, YAML

    Advanced · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Track and Evaluate ML Model Experiments

    Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Model Training, Model Deployment, Version Control, Large Language Modeling, Predictive Modeling, Data Management, Dashboard, Interactive Data Visualization, Machine Learning, Record Keeping, Performance Analysis

    Intermediate · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Automate, Analyze, and Evaluate ML Experiments

    Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Key Performance Indicators (KPIs), Business Metrics, Performance Analysis, Apache Airflow, Performance Measurement, Responsible AI, Test Execution Engine, Performance Metric, Test Automation, Verification And Validation, Content Performance Analysis, Automation, Statistical Methods, Quality Assessment, Gap Analysis, Cost Benefit Analysis, Research Design, Quantitative Research

    Intermediate · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • W

    Whizlabs

    AWS: Machine Learning & MLOps Foundations

    Skills you'll gain: MLOps (Machine Learning Operations), Data Preprocessing, AWS SageMaker, Model Evaluation, Model Deployment, Artificial Intelligence and Machine Learning (AI/ML), Amazon Web Services, Model Training, Predictive Modeling, Machine Learning Methods, Applied Machine Learning, Data Processing, Machine Learning, Supervised Learning, Machine Learning Algorithms, Unsupervised Learning, Classification Algorithms

    ★ 4.3 (6) · Intermediate · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Learn to Choose the Right ML Model

    Skills you'll gain: Model Training, Model Deployment, MLOps (Machine Learning Operations), Applied Machine Learning, Model Evaluation, Scikit Learn (Machine Learning Library), Machine Learning Methods, Machine Learning, Predictive Modeling, Scenario Testing, Machine Learning Algorithms, Feature Engineering, Statistical Machine Learning, Responsible AI, Regression Analysis, Classification Algorithms, Continuous Monitoring

    Intermediate · Course · 1 - 4 Weeks

    Category: New
    New
    Category: Preview
    Preview
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Apply SOLID Design to Optimize Java ML

    Skills you'll gain: Apache Maven, Maintainability, Java Programming, Gradle, Software Design, Software Architecture, Software Design Patterns, Build Tools, Object Oriented Design, Object Oriented Programming (OOP), Machine Learning Methods, Integration Testing, Dependency Analysis, User Interface (UI) Design, Design Strategies, Design Elements And Principles, Program Evaluation, Automation

    Advanced · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Automate, Validate, and Promote ML Models Safely

    Skills you'll gain: MLOps (Machine Learning Operations), Responsible AI, CI/CD, Data Ethics, Model Deployment, Model Training, Continuous Integration, Continuous Delivery, Continuous Deployment, Cloud Platforms, Model Evaluation, Automation, Data Governance, Data Pipelines, Performance Tuning, Continuous Monitoring, Performance Analysis, Analysis

    Intermediate · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • W

    Whizlabs

    AWS: ML Workflows with SageMaker, Storage & Security

    Skills you'll gain: AWS SageMaker, AWS Kinesis, Amazon Web Services, Amazon Redshift, Cloud Security, MLOps (Machine Learning Operations), Amazon S3, Model Training, AWS Identity and Access Management (IAM), Model Deployment, Real Time Data, Feature Engineering, Cloud Storage, Data Storage, Data Security, Encryption, Key Management

    Intermediate · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
1…678…117

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

  • Interpretable Machine Learning Applications: Part 2: Coursera
  • Microsoft Azure for AI and Machine Learning: Microsoft
  • Apply Test-Driven ML Code: Coursera
  • Machine Learning Operations (MLOps) with Vertex AI: Manage Features: Google Cloud
  • Automate, Evaluate and Deploy ML Models Confidently: Coursera
  • Track and Evaluate ML Model Experiments: Coursera
  • Automate, Analyze, and Evaluate ML Experiments: Coursera
  • AWS: Machine Learning & MLOps Foundations: Whizlabs
  • Learn to Choose the Right ML Model: Coursera
  • Apply SOLID Design to Optimize Java ML: Coursera

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