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  • Ml Explainability

Results for "ml explainability"


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    Duke University

    Explainable AI (XAI)

    Skills you'll gain: Responsible AI, Large Language Modeling, Data Ethics, Decision Tree Learning, AI Security, Regression Analysis, Generative AI, Artificial Intelligence, Predictive Modeling, AI Product Strategy, Statistical Modeling, Python Programming, Machine Learning, Model Evaluation, Applied Machine Learning, Logistic Regression, Machine Learning Methods, Deep Learning, Visualization (Computer Graphics), Data Literacy

    4.7
    Rating, 4.7 out of 5 stars
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    80 reviews

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
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    Microsoft

    Microsoft AI & ML Engineering

    Skills you'll gain: Unsupervised Learning, Model Deployment, 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), Generative Adversarial Networks (GANs), Infrastructure Architecture, LLM Application, Responsible AI, Generative AI Agents, Applied Machine Learning, Azure DevOps, Reinforcement Learning, Data Preprocessing

    4.6
    Rating, 4.6 out of 5 stars
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    323 reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: New
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    C

    Coursera

    Level Up: Java-Powered Machine Learning

    Skills you'll gain: Model Evaluation, Data Preprocessing, JUnit, Build Tools, Java Programming, MLOps (Machine Learning Operations), Java, Performance Tuning, Decision Tree Learning, Classification And Regression Tree (CART), Apache Maven, Data Structures, Random Forest Algorithm, Gradle, Data Pipelines, Software Architecture, Software Design, Object Oriented Programming (OOP), Apache, Machine Learning

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
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    Status: Free Trial
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    Coursera

    ML Production Systems

    Skills you'll gain: Unit Testing, Test Driven Development (TDD), Software Testing, Scalability, Dashboard, MLOps (Machine Learning Operations), Testability, Kubernetes, Version Control, Model Deployment, Performance Tuning, Software Engineering, PyTorch (Machine Learning Library), Tensorflow, CI/CD, Containerization, Docker (Software), Scikit Learn (Machine Learning Library), Git (Version Control System), Python Programming

    Intermediate · Specialization · 1 - 3 Months

  • Status: New
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    Status: Free Trial
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    Coursera

    Engineer AI Models: Explain, Tune & Experiment

    Skills you'll gain: Feature Engineering, Fraud detection, Jupyter, Program Management, Responsible AI, Model Evaluation, Project Management, Performance Improvement, Performance Metric, Business Analytics, Credit Risk, Performance Analysis, Performance Tuning, Machine Learning Methods, Test Planning, Test Engineering, Research Design, Technical Communication

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    D

    Duke University

    MLOps | Machine Learning Operations

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Cloud Deployment, Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Hugging Face, Responsible AI, Data Manipulation, Exploratory Data Analysis, Containerization, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis

    4.2
    Rating, 4.2 out of 5 stars
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    582 reviews

    Advanced · Specialization · 3 - 6 Months

What brings you to Coursera today?

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    W

    Whizlabs

    Exam Prep MLS-C01: AWS Certified Specialty Machine Learning

    Skills you'll gain: AWS Kinesis, Model Evaluation, AWS SageMaker, Machine Learning Algorithms, Data Collection, Amazon Redshift, MLOps (Machine Learning Operations), Image Analysis, Reinforcement Learning, Amazon Web Services, Model Deployment, Data Preprocessing, Scalability, Classification Algorithms, Forecasting, Feature Engineering, Algorithms, Data Analysis, Predictive Modeling, Data Modeling

    3.9
    Rating, 3.9 out of 5 stars
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    42 reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
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    Coursera

    Automate, Evaluate and Deploy ML Models Confidently

    Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Scalability, CI/CD, Continuous Deployment, Application Deployment, DevOps, Artificial Intelligence and Machine Learning (AI/ML), Model Evaluation, Continuous Integration, Performance Measurement, Business Metrics, Process Optimization, Verification And Validation, Automation, Key Performance Indicators (KPIs), Performance Analysis, Data-Driven Decision-Making

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Machine Learning on Google Cloud

    Skills you'll gain: Feature Engineering, Generative AI, Model Deployment, Tensorflow, Google Cloud Platform, Keras (Neural Network Library), Data Preprocessing, Data Quality, MLOps (Machine Learning Operations), Exploratory Data Analysis, Machine Learning, Applied Machine Learning, Model Evaluation, Scikit Learn (Machine Learning Library), Data Cleansing, AI Enablement, Prompt Engineering, Cloud Deployment, AI Workflows, Cloud Computing

    4.4
    Rating, 4.4 out of 5 stars
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    3.8K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
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    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, Performance Measurement, Responsible AI, Test Execution Engine, Performance Metric, Test Automation, Feature Engineering, Verification And Validation, Content Performance Analysis, Machine Learning, Data Ethics, Quality Assessment, Gap Analysis, Cost Benefit Analysis, Research Design, Quantitative Research

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Apply Test-Driven ML Code

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

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Optimize and Manage Your ML Codebase

    Skills you'll gain: MLOps (Machine Learning Operations), Version Control, Model Deployment, CI/CD, Git (Version Control System), Continuous Deployment, Performance Tuning, Continuous Integration, Software Development Methodologies, Model Evaluation, Software Versioning, Release Management, Continuous Delivery, Performance Testing, PyTorch (Machine Learning Library), Performance Improvement

    Intermediate · Course · 1 - 4 Weeks

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

  • Explainable AI (XAI): Duke University
  • Microsoft AI & ML Engineering: Microsoft
  • Level Up: Java-Powered Machine Learning: Coursera
  • ML Production Systems: Coursera
  • Engineer AI Models: Explain, Tune & Experiment: Coursera
  • MLOps | Machine Learning Operations: Duke University
  • Exam Prep MLS-C01: AWS Certified Specialty Machine Learning: Whizlabs
  • Automate, Evaluate and Deploy ML Models Confidently: Coursera
  • Machine Learning on Google Cloud: Google Cloud
  • Automate, Analyze, and Evaluate ML Experiments: Coursera

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