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  • Explainable Machine Learning Models

Results for "explainable machine learning models"


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

    Coursera

    ML Model Training & Validation

    Skills you'll gain: MLOps (Machine Learning Operations), Data Pipelines, Model Evaluation, Systems Design, Transfer Learning, Data Preprocessing, Data Quality, Feature Engineering, Deep Learning, Python Programming, Data Validation, Scikit Learn (Machine Learning Library), Applied Machine Learning, Predictive Modeling, Software Engineering, Debugging, Supervised Learning, Git (Version Control System), Performance Metric, Statistical Analysis

    Intermediate · Specialization · 1 - 3 Months

  • Status: Preview
    Preview
    I

    IBM

    Machine Learning Introduction for Everyone

    Skills you'll gain: Model Evaluation, Predictive Modeling, Machine Learning, Supervised Learning, Applied Machine Learning, Data Science, Artificial Intelligence, Deep Learning, Classification Algorithms, Unsupervised Learning, Regression Analysis, Reinforcement Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    308 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: New
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    Coursera

    Probabilistic Graphical Models: A Compact Introduction

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

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
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    Coursera

    Training, Evaluating, and Monitoring Machine Learning Models

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

    Intermediate · Course · 1 - 3 Months

  • Status: New
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    Coursera

    ML: Build, Train, Justify Models

    Skills you'll gain: Predictive Modeling, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Statistical Modeling, Decision Tree Learning, Report Writing

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    D

    Duke University

    Introduction to Machine Learning

    Skills you'll gain: PyTorch (Machine Learning Library), Logistic Regression, Transfer Learning, Reinforcement Learning, Convolutional Neural Networks, Deep Learning, Image Analysis, Applied Machine Learning, Natural Language Processing, Machine Learning, Recurrent Neural Networks (RNNs), Artificial Neural Networks, Supervised Learning, Unsupervised Learning, Python Programming, Computer Vision, Medical Imaging

    4.7
    Rating, 4.7 out of 5 stars
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    3.8K reviews

    Intermediate · Course · 1 - 3 Months

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

    Coursera

    Debug ML Code: Fix, Trace & Evaluate

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

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
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    Edureka

    Applied Machine Learning Without Coding

    Skills you'll gain: Model Evaluation, Classification Algorithms, Regression Analysis, Data Science, Statistical Modeling, Predictive Modeling, Exploratory Data Analysis, Machine Learning, Data Analysis, Applied Machine Learning, Machine Learning Algorithms, Feature Engineering, Random Forest Algorithm, Supervised Learning, Logistic Regression, Data Processing, Data Preprocessing, Predictive Analytics, Data Manipulation, Data Visualization

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    S

    Simplilearn

    AI ML with Deep Learning and Supervised Models

    Skills you'll gain: Supervised Learning, Data Modeling, Unsupervised Learning, Applied Machine Learning, Data Analysis, Recurrent Neural Networks (RNNs), Model Deployment, Reinforcement Learning, Artificial Intelligence, Classification Algorithms, Classification And Regression Tree (CART), Tensorflow, Machine Learning Algorithms, Keras (Neural Network Library), Artificial Neural Networks, Deep Learning, Machine Learning, Decision Tree Learning, Predictive Analytics, Regression Analysis

    3.9
    Rating, 3.9 out of 5 stars
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    11 reviews

    Beginner · Specialization · 1 - 3 Months

  • 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, Predictive Modeling, Artificial Intelligence, Machine Learning, Statistical Modeling, Python Programming, Logistic Regression, Deep Learning, Artificial Neural Networks

    4.6
    Rating, 4.6 out of 5 stars
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    29 reviews

    Intermediate · Course · 1 - 4 Weeks

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

    Coursera

    Validate, Analyze, and Monitor ML Models

    Skills you'll gain: Verification And Validation, Experimentation, Performance Testing, Benchmarking, Performance Analysis, Technical Communication

    Intermediate · Course · 1 - 4 Weeks

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

    Evaluate, Analyze, and Model Performance

    Skills you'll gain: Performance Metric, Predictive Modeling, Data-Driven Decision-Making, Failure Analysis, Statistical Analysis, Technical Communication, Statistical Hypothesis Testing

    Intermediate · Course · 1 - 4 Weeks

1234…732

In summary, here are 10 of our most popular explainable machine learning models courses

  • ML Model Training & Validation: Coursera
  • Machine Learning Introduction for Everyone: IBM
  • Probabilistic Graphical Models: A Compact Introduction: Coursera
  • Training, Evaluating, and Monitoring Machine Learning Models: Coursera
  • ML: Build, Train, Justify Models: Coursera
  • Introduction to Machine Learning: Duke University
  • Debug ML Code: Fix, Trace & Evaluate: Coursera
  • Applied Machine Learning Without Coding: Edureka
  • AI ML with Deep Learning and Supervised Models: Simplilearn
  • Interpretable Machine Learning: Duke University

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