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  • Explainable Machine Learning Models


Results for "explainable machine learning models"


  • Status: Free Trial
    Free Trial
    S

    Stanford University

    Probabilistic Graphical Models 3: Learning

    Skills you'll gain: Bayesian Network, Applied Machine Learning, Machine Learning Algorithms, Bayesian Statistics, Markov Model, Machine Learning, Statistical Modeling, Probability Distribution, Statistical Methods, Algorithms, Model Evaluation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    304 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Preview
    Preview
    N

    National Taiwan University

    機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations

    Skills you'll gain: Classification Algorithms, Supervised Learning, Machine Learning, Machine Learning Algorithms, Logistic Regression, Data Validation, Applied Machine Learning, Data Preprocessing, Model Evaluation, Algorithms, Programming Principles, Regression Analysis, Feature Engineering, Statistical Methods

    4.9
    Rating, 4.9 out of 5 stars
    ·
    331 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado System

    Machine Learning for Marketers

    Skills you'll gain: Classification And Regression Tree (CART), AI Personalization, Marketing Analytics, Unsupervised Learning, Customer Analysis, Predictive Analytics, Applied Machine Learning, Supervised Learning, Dimensionality Reduction, Marketing Effectiveness, Marketing Strategies, Data-Driven Decision-Making, Strategic Marketing, Campaign Management, Customer experience improvement, Personalized Service, Customer Insights, Model Evaluation, Machine Learning

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Interpretable Machine Learning Applications: Part 2

    Skills you'll gain: Model Evaluation, Applied Machine Learning, Data Preprocessing, Classification Algorithms, Random Forest Algorithm, Predictive Modeling, Regression Analysis, Decision Tree Learning, Machine Learning, Scikit Learn (Machine Learning Library), Exploratory Data Analysis

    4.2
    Rating, 4.2 out of 5 stars
    ·
    27 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: New
    New
    Status: Preview
    Preview
    C

    Coursera

    Learn to Choose the Right ML Model

    Skills you'll gain: MLOps (Machine Learning Operations), Applied Machine Learning, Model Evaluation, Scikit Learn (Machine Learning Library), Machine Learning, Predictive Modeling, Scenario Testing, Machine Learning Algorithms, Responsible AI, Regression Analysis, Classification And Regression Tree (CART), Case Studies, Continuous Monitoring, Performance Metric

    Intermediate · Course · 1 - 4 Weeks

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

    Coursera

    Automate, Validate, and Promote ML Models Safely

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

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    S

    Stanford University

    Probabilistic Graphical Models 2: Inference

    Skills you'll gain: Bayesian Network, Machine Learning Methods, Statistical Inference, Markov Model, Graph Theory, Sampling (Statistics), Applied Machine Learning, Statistical Methods, Probability & Statistics, Algorithms, Probability Distribution, Machine Learning Algorithms, Computational Thinking

    4.6
    Rating, 4.6 out of 5 stars
    ·
    489 reviews

    Advanced · Course · 1 - 3 Months

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

    Coursera

    Engineer AI Models: Explain, Tune & Experiment

    Skills you'll gain: Feature Engineering, Fraud detection, Jupyter, Program Management, Responsible AI, Model Evaluation, Performance Improvement, Project Management, 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

  • C

    Coursera

    Interpretable Machine Learning Applications: Part 1

    Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Model Evaluation, Random Forest Algorithm, Responsible AI, Data Import/Export, Machine Learning, Classification Algorithms

    4.4
    Rating, 4.4 out of 5 stars
    ·
    80 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: New
    New
    Status: Free Trial
    Free Trial
    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, 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: Free Trial
    Free Trial
    E

    EDUCBA

    PySpark: Apply & Evaluate Predictive ML Models

    Skills you'll gain: Model Evaluation, PySpark, Apache Spark, Logistic Regression, Predictive Modeling, Applied Machine Learning, Unsupervised Learning, Decision Tree Learning, Predictive Analytics, Random Forest Algorithm, Regression Analysis, Classification Algorithms, Machine Learning Algorithms, Data Pipelines

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    Duke University

    MLOps Platforms: Amazon SageMaker and Azure ML

    Skills you'll gain: AWS SageMaker, MLOps (Machine Learning Operations), Microsoft Azure, Model Deployment, Exploratory Data Analysis, Data Pipelines, Amazon Web Services, Feature Engineering, Cloud Platforms, Model Evaluation, Data Preprocessing, Cloud Deployment, Data Analysis, Serverless Computing, Machine Learning, Python Programming

    3.5
    Rating, 3.5 out of 5 stars
    ·
    56 reviews

    Advanced · Course · 1 - 3 Months

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

  • Probabilistic Graphical Models 3: Learning: Stanford University
  • 機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations: National Taiwan University
  • Machine Learning for Marketers: University of Colorado System
  • Interpretable Machine Learning Applications: Part 2: Coursera
  • Learn to Choose the Right ML Model: Coursera
  • Automate, Validate, and Promote ML Models Safely: Coursera
  • Probabilistic Graphical Models 2: Inference: Stanford University
  • Engineer AI Models: Explain, Tune & Experiment: Coursera
  • Interpretable Machine Learning Applications: Part 1: Coursera
  • Automate, Analyze, and Evaluate ML Experiments: Coursera

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