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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

  • 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

  • Status: Top AI Program
    Top AI Program
    C

    Coursera

    Machine Learning with Scikit-learn, PyTorch & Hugging Face

    Skills you'll gain: Generative AI, Model Evaluation, Supervised Learning, Generative Model Architectures, Recurrent Neural Networks (RNNs), Unsupervised Learning, Data Preprocessing, Large Language Modeling, Time Series Analysis and Forecasting, Exploratory Data Analysis, LLM Application, Applied Machine Learning, Generative Adversarial Networks (GANs), Retrieval-Augmented Generation, Data Collection, Machine Learning Algorithms, Convolutional Neural Networks, Model Deployment, Transfer Learning, Hugging Face

    4.6
    Rating, 4.6 out of 5 stars
    ·
    22 reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • 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

  • 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

  • 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

    ML Data Pipelines and Communicating AI Insights

    Skills you'll gain: Feature Engineering, Extract, Transform, Load, Data Pipelines, Data Transformation, Model Evaluation, Pandas (Python Package), Data Storytelling, Data Presentation, Data Preprocessing, PySpark, Data Quality, Apache Spark, Data-Driven Decision-Making, A/B Testing, Data Analysis, Data Visualization, Data Governance, Data Cleansing, Exploratory Data Analysis, Machine Learning

    Intermediate · Course · 1 - 3 Months

  • J

    Johns Hopkins University

    Applied Machine Learning

    Skills you'll gain: Computer Vision, Model Evaluation, PyTorch (Machine Learning Library), Supervised Learning, Unsupervised Learning, Image Analysis, Applied Machine Learning, Data Preprocessing, Dimensionality Reduction, Reinforcement Learning, Feature Engineering, Machine Learning Algorithms, Convolutional Neural Networks, Regression Analysis, Data Processing, Machine Learning, Data Mining, Data Cleansing, Deep Learning, Artificial Neural Networks

    3.6
    Rating, 3.6 out of 5 stars
    ·
    15 reviews

    Intermediate · Specialization · 3 - 6 Months

  • 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

  • G

    Google Cloud

    Machine Learning on Google Cloud

    Skills you'll gain: Feature Engineering, Generative AI, Model Deployment, Tensorflow, Google Cloud Platform, Keras (Neural Network Library), Machine Learning, Data Preprocessing, MLOps (Machine Learning Operations), Model Evaluation, Applied Machine Learning, Data Cleansing, Data Quality, AI Enablement, Prompt Engineering, Cloud Deployment, Supervised Learning, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Cloud Computing

    4.4
    Rating, 4.4 out of 5 stars
    ·
    3.8K reviews

    Intermediate · Specialization · 3 - 6 Months

  • C

    Coursera

    Model Training & Evaluation

    Skills you'll gain: Supervised Learning, Statistical Machine Learning, Scikit Learn (Machine Learning Library), Applied Machine Learning, Machine Learning

    Intermediate · Course · 1 - 4 Weeks

  • 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

1234…624

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

  • The Nuts and Bolts of Machine Learning: Google
  • Machine Learning for All: University of London
  • Machine Learning with Scikit-learn, PyTorch & Hugging Face: Coursera
  • Machine Learning Introduction for Everyone: IBM
  • Training, Evaluating, and Monitoring Machine Learning Models: Coursera
  • Building, Optimizing, and Validating Machine Learning Models: Coursera
  • ML Data Pipelines and Communicating AI Insights : Coursera
  • Applied Machine Learning: Johns Hopkins University
  • Validate, Analyze, and Monitor ML Models: Coursera
  • Machine Learning on Google Cloud: Google Cloud

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