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  • Model Interpretability

Results for "model interpretability"


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    Duke University

    Explainable AI (XAI)

    Skills you'll gain: Responsible AI, Large Language Modeling, Data Ethics, Decision Tree Learning, Regression Analysis, Generative AI, Artificial Intelligence, AI literacy, Decision Intelligence, Applied Machine Learning, Generative Model Architectures, Statistical Modeling, Python Programming, Machine Learning, Model Evaluation, Embeddings, Image Analysis, Machine Learning Methods, Scientific Visualization, Deep Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    83 reviews

    Intermediate · Specialization · 1 - 3 Months

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    Coursera

    Responsible AI, Explainability & Deployment

    Skills you'll gain: Decision Intelligence, Responsible AI, Apache Kafka, Data Ethics, Operations Research, Data Pipelines, Model Deployment, Apache Spark, Real Time Data, Revenue Management, Market Dynamics, Supply Chain Planning, Supply Chain, Logistics, Compliance Management, Information Privacy, People Analytics, Regulatory Compliance, General Data Protection Regulation (GDPR), Python Programming

    Intermediate · Course · 3 - 6 Months

  • Status: New
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    Coursera

    Explain Black-Box Models

    Skills you'll gain: Stakeholder Communications, Stakeholder Engagement, Data Storytelling, Stakeholder Management, Stakeholder Analysis, Data Presentation, Data-Driven Decision-Making, Business Communication, Model Evaluation, Responsible AI

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Coursera

    Advanced Model Architectures & Language AI

    Skills you'll gain: Classification And Regression Tree (CART), Decision Tree Learning, Large Language Modeling, Retrieval-Augmented Generation, LLM Application, Data Analysis, Applied Machine Learning, Keras (Neural Network Library), Machine Learning Methods, Model Evaluation, Model Training, Fine-tuning, Model Deployment, Generative AI, Text Mining, Prompt Engineering, Deep Learning, Random Forest Algorithm, Machine Learning, MLOps (Machine Learning Operations)

    Intermediate · Course · 3 - 6 Months

  • Status: New
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    Coursera

    Probabilistic Graphical Models: A Compact Introduction

    Skills you'll gain: Bayesian Network, Bayesian Statistics, Network Model, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Markov Model, Statistical Modeling, Statistical Inference, Graph Theory, Probability & Statistics, Sampling (Statistics), Algorithms

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Coursera

    Training, Evaluating, and Monitoring Machine Learning Models

    Skills you'll gain: Model Evaluation, Model Training, MLOps (Machine Learning Operations), System Monitoring, Continuous Monitoring, Model Deployment, Verification And Validation, Performance Metric, A/B Testing, Statistical Methods, Failure Analysis, Statistical Hypothesis Testing, Applied Machine Learning, Statistical Analysis, Scikit Learn (Machine Learning Library), Benchmarking

    Intermediate · Course · 1 - 3 Months

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    Stanford University

    Probabilistic Graphical Models

    Skills you'll gain: Bayesian Network, Applied Machine Learning, Decision Intelligence, Bayesian Statistics, Graph Theory, Machine Learning Algorithms, Probability Distribution, Network Model, Statistical Modeling, Machine Learning Methods, Markov Model, Decision Support Systems, Machine Learning, Unsupervised Learning, Probability & Statistics, Network Analysis, Statistical Inference, Model Training, Statistical Machine Learning, Model Optimization

    4.6
    Rating, 4.6 out of 5 stars
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    1.5K reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: New
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    Coursera

    Calibrate and Serve Confident AI Predictions

    Skills you'll gain: Model Evaluation, MLOps (Machine Learning Operations), AI Workflows, Applied Machine Learning, Model Optimization, Data Pipelines, Responsible AI, Statistical Modeling

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Coursera

    Predict and Validate Regression Models in R

    Skills you'll gain: Regression Analysis, Predictive Modeling, Model Evaluation, Statistical Modeling, Predictive Analytics, R Programming, Financial Forecasting, Statistical Methods, Model Training, Data Validation, Verification And Validation, Plot (Graphics), Performance Metric

    Beginner · Course · 1 - 4 Weeks

  • Status: New
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    Coursera

    Optimize AI: Build & Evaluate Predictive Models

    Skills you'll gain: Machine Learning Methods, Predictive Modeling, Model Training, Statistical Machine Learning, Machine Learning Software, Model Optimization, Performance Analysis, Performance Metric, Performance Improvement

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
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    Board Infinity

    Transformers and NLP: Fine-Tuning Models with Hugging Face

    Skills you'll gain: Model Evaluation, Fine-tuning, Model Optimization, Hugging Face, Model Deployment, Model Training, Transfer Learning, Natural Language Processing, MLOps (Machine Learning Operations), Large Language Modeling, Performance Tuning, Generative Model Architectures, Application Deployment, Data Preprocessing, Data Pipelines, Embeddings, Version Control, Git (Version Control System)

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    Duke University

    Interpretable Machine Learning

    Skills you'll gain: Responsible AI, Large Language Modeling, Decision Tree Learning, Data Ethics, Regression Analysis, Artificial Intelligence, Machine Learning, Applied Machine Learning, Statistical Modeling, Python Programming, Embeddings, Deep Learning, Machine Learning Algorithms, Artificial Neural Networks

    4.6
    Rating, 4.6 out of 5 stars
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    29 reviews

    Intermediate · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular model interpretability courses

  • Explainable AI (XAI): Duke University
  • Responsible AI, Explainability & Deployment: Coursera
  • Explain Black-Box Models: Coursera
  • Advanced Model Architectures & Language AI: Coursera
  • Probabilistic Graphical Models: A Compact Introduction: Coursera
  • Training, Evaluating, and Monitoring Machine Learning Models: Coursera
  • Probabilistic Graphical Models: Stanford University
  • Calibrate and Serve Confident AI Predictions: Coursera
  • Predict and Validate Regression Models in R: Coursera
  • Optimize AI: Build & Evaluate Predictive Models: Coursera

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