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  • Machine Learning Interpretability

Results for "machine learning interpretability"


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    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
    ·
    309 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: New
    New
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    C

    Coursera

    Building, Optimizing, and Validating Machine Learning Models

    Intermediate · Course · 1 - 3 Months

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    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

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    O

    O.P. Jindal Global University

    Machine Learning

    Skills you'll gain: Model Evaluation, Supervised Learning, Scikit Learn (Machine Learning Library), Tensorflow, Applied Machine Learning, Artificial Neural Networks, Python Programming, NumPy, Matplotlib, Deep Learning, Image Analysis, Machine Learning, Embeddings, Pandas (Python Package), Convolutional Neural Networks, Natural Language Processing, Regression Analysis

    Build toward a degree

    3.9
    Rating, 3.9 out of 5 stars
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    9 reviews

    Beginner · Course · 1 - 3 Months

  • Status: New
    New
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    C

    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

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

    Coursera

    Validate and Explain Your ML Models

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

    Intermediate · Course · 1 - 4 Weeks

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

    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
    P

    Politecnico di Milano

    Machine Learning: an overview

    Skills you'll gain: Machine Learning Methods, Unsupervised Learning, Supervised Learning, Machine Learning Algorithms, Machine Learning, Reinforcement Learning, Dimensionality Reduction, Model Evaluation, Classification Algorithms, Algorithms

    4.6
    Rating, 4.6 out of 5 stars
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    209 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
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    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

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    E

    EDUCBA

    AI & Machine Learning: Apply, Build & Solve

    Skills you'll gain: Artificial Intelligence, Bayesian Network, Applied Machine Learning, Computational Logic, Machine Learning, Unsupervised Learning, Bayesian Statistics, Artificial Neural Networks, Reinforcement Learning, Markov Model, Algorithms, Probability & Statistics, Decision Making

    5
    Rating, 5 out of 5 stars
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    10 reviews

    Mixed · Course · 1 - 3 Months

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    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: Free Trial
    Free Trial
    F

    Fractal Analytics

    Foundations of Machine Learning

    Skills you'll gain: Model Evaluation, Model Deployment, Machine Learning, Supervised Learning, Regression Analysis, Decision Tree Learning, Feature Engineering, Data Preprocessing, Unsupervised Learning, Predictive Modeling, Logistic Regression, Anomaly Detection, Classification Algorithms

    4.5
    Rating, 4.5 out of 5 stars
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    14 reviews

    Beginner · Course · 1 - 3 Months

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

  • Machine Learning Introduction for Everyone: IBM
  • Building, Optimizing, and Validating Machine Learning Models: Coursera
  • Validate, Analyze, and Monitor ML Models: Coursera
  • Machine Learning: O.P. Jindal Global University
  • Evaluate, Analyze, and Model Performance: Coursera
  • Validate and Explain Your ML Models: Coursera
  • Applied Machine Learning Without Coding: Edureka
  • Machine Learning: an overview: Politecnico di Milano
  • Calibrate and Serve Confident AI Predictions: Coursera
  • AI & Machine Learning: Apply, Build & Solve: EDUCBA

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