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  • Machine Learning Interpretability

Results for "machine learning interpretability"


  • G

    Google

    The Nuts and Bolts of Machine Learning

    Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Random Forest Algorithm, Data Analysis, Predictive Modeling, Model Evaluation, Bayesian Network, Python Programming, Statistical Modeling, Classification Algorithms

    4.8
    Rating, 4.8 out of 5 stars
    ·
    611 reviews

    Advanced · Course · 1 - 3 Months

  • D

    Duke University

    Explainable Machine Learning (XAI)

    Skills you'll gain: Responsible AI, Large Language Modeling, Generative AI, Artificial Intelligence, Model Evaluation, Python Programming, Applied Machine Learning, Machine Learning, Visualization (Computer Graphics), Deep Learning, Plot (Graphics), Artificial Neural Networks

    4.7
    Rating, 4.7 out of 5 stars
    ·
    27 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Trending in AI
    Trending in AI
    I

    Imperial College London

    Mathematics for Machine Learning

    Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Data Preprocessing, Unsupervised Learning, Feature Engineering, Machine Learning Algorithms, Jupyter, Advanced Mathematics, Statistics, Artificial Neural Networks, Algorithms, Mathematical Modeling, Python Programming, Derivatives

    4.6
    Rating, 4.6 out of 5 stars
    ·
    15K reviews

    Beginner · Specialization · 3 - 6 Months

  • U

    University of London

    Machine Learning for All

    Skills you'll gain: Data Preprocessing, Machine Learning, Artificial Intelligence, Model Evaluation, Data Analysis, Image Analysis, Data Collection, Classification Algorithms

    Build toward a degree

    4.7
    Rating, 4.7 out of 5 stars
    ·
    3.5K reviews

    Beginner · Course · 1 - 4 Weeks

  • 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
    ·
    307 reviews

    Beginner · Course · 1 - 4 Weeks

  • 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
    ·
    3.8K reviews

    Intermediate · Course · 1 - 3 Months

  • C

    Coursera

    Automate, Optimize, and Monitor ML Models

    Skills you'll gain: Verification And Validation, Data Pipelines

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Calibrate and Serve Confident AI Predictions

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

    Intermediate · Course · 1 - 4 Weeks

  • C

    Coursera

    Building, Optimizing, and Validating Machine Learning Models

    Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Applied Machine Learning, Predictive Modeling, Feature Engineering, Workflow Management, Verification And Validation, Business Logic, Machine Learning, Supervised Learning, Statistical Machine Learning, Statistical Modeling, Performance Tuning, Machine Learning Algorithms, Scikit Learn (Machine Learning Library), Benchmarking, Random Forest Algorithm, Performance Analysis, Cost Management, Resource Utilization

    Intermediate · Course · 1 - 3 Months

  • C

    Coursera

    Validate and Explain Your ML Models

    Skills you'll gain: Verification And Validation, Sampling (Statistics), Performance Testing, Statistical Machine Learning, Test Data, Machine Learning

    Intermediate · Course · 1 - 4 Weeks

  • 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

  • C

    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

1234…620

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

  • The Nuts and Bolts of Machine Learning: Google
  • Explainable Machine Learning (XAI): Duke University
  • Mathematics for Machine Learning: Imperial College London
  • Machine Learning for All: University of London
  • Machine Learning Introduction for Everyone: IBM
  • Introduction to Machine Learning: Duke University
  • Automate, Optimize, and Monitor ML Models: Coursera
  • Calibrate and Serve Confident AI Predictions: Coursera
  • Building, Optimizing, and Validating Machine Learning Models: Coursera
  • Validate and Explain Your ML Models: Coursera

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