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  • Machine Learning Interpretability

Results for "machine learning interpretability"


  • C

    Coursera

    Interpretable machine learning applications: Part 3

    Skills you'll gain: Artificial Neural Networks, Tensorflow, Keras (Neural Network Library), Data-Driven Decision-Making, Applied Machine Learning, Machine Learning Software, Deep Learning, Machine Learning, Feature Engineering, Risking, Model Evaluation, Mortgage Loans, Consumer Lending

    4.5
    Rating, 4.5 out of 5 stars
    ·
    27 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Machine Learning in Python: Analyze & Apply

    Skills you'll gain: Matplotlib, Plot (Graphics), NumPy, Pandas (Python Package), Applied Machine Learning, Python Programming, Scikit Learn (Machine Learning Library), Data Visualization, Supervised Learning, Feature Engineering, Machine Learning, Natural Language Processing, Model Optimization, Machine Learning Algorithms, Text Mining, Data Manipulation, Predictive Modeling, Model Training, Unsupervised Learning, Data Management

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Decoding AI: A Deep Dive into AI Models and Predictions

    Skills you'll gain: Generative AI, Model Evaluation, AI literacy, Data Ethics, Data Analysis, Model Training, Responsible AI, Data Literacy, Discussion Facilitation, Artificial Intelligence, Big Data, Predictive Modeling, Machine Learning, Social Impact

    4.8
    Rating, 4.8 out of 5 stars
    ·
    26 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Machine Learning with Python & Statistics

    Skills you'll gain: Sampling (Statistics), Data Mining, Statistical Hypothesis Testing, Probability, Statistical Machine Learning, Probability & Statistics, Linear Algebra, Statistical Methods, Statistical Analysis, Statistical Inference, Data Analysis, Probability Distribution, Data Science, Statistics, Machine Learning Methods, Applied Machine Learning, Unsupervised Learning, Machine Learning Algorithms, Machine Learning, Supervised Learning

    Mixed · Course · 1 - 4 Weeks

  • C

    Coursera

    Interpretable Machine Learning Applications: Part 4

    Skills you'll gain: Predictive Modeling, Applied Machine Learning, Data Preprocessing, Data Analysis, Data Import/Export, Google Cloud Platform, Model Evaluation, Decision Tree Learning, Model Training, Data Processing, Analysis, Machine Learning, Classification Algorithms, Machine Learning Methods, Random Forest Algorithm, Statistical Visualization, Software Visualization

    4.7
    Rating, 4.7 out of 5 stars
    ·
    22 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Preview
    Preview
    N

    National Taiwan University

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

    Skills you'll gain: Machine Learning Algorithms, Model Evaluation, Classification Algorithms, Machine Learning Methods, Model Training, Algorithms, Supervised Learning, Logistic Regression, Machine Learning, Statistical Machine Learning, Applied Machine Learning, Data Validation, Regression Analysis, Feature Engineering, Statistical Methods, Model Optimization, Verification And Validation, Linear Algebra, Data Transformation

    4.9
    Rating, 4.9 out of 5 stars
    ·
    331 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Machine Learning with R: Build, Analyze & Predict

    Skills you'll gain: Data Analysis, Machine Learning Algorithms, Statistical Analysis, Probability & Statistics, Probability Distribution, R Programming, Machine Learning Methods, Statistical Methods, R (Software), Applied Machine Learning, Statistical Machine Learning, Statistics, Statistical Modeling, Machine Learning, Statistical Inference, Classification Algorithms, Statistical Programming, Correlation Analysis, Data Manipulation, Supervised Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    16 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: New
    New
    P

    Packt

    Decoding Large Language Models

    Skills you'll gain: Large Language Modeling, LLM Application, Fine-tuning, Model Deployment, Model Training, Transfer Learning, Generative Model Architectures, Prompt Engineering, Model Optimization, Generative AI, Model Evaluation, Deep Learning, Natural Language Processing, Recurrent Neural Networks (RNNs), AI Security, Responsible AI, Scalability, Machine Learning

    Advanced · Course · 3 - 6 Months

  • Status: Free
    Free
    D

    DeepLearning.AI

    Evaluating and Debugging Generative AI

    Skills you'll gain: MLOps (Machine Learning Operations), Large Language Modeling, LLM Application, Jupyter, AI Workflows, Model Training, Software Versioning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    10 reviews

    Intermediate · Project · Less Than 2 Hours

  • C

    Coursera

    Interpretable machine learning applications: Part 5

    Skills you'll gain: Model Evaluation, Responsible AI, Exploratory Data Analysis, Histogram, Predictive Modeling, Data Visualization, Predictive Analytics, Data Preprocessing, Machine Learning, Policy Analysis, Statistical Methods, Data Science, Descriptive Statistics, Data Ethics, Economics, Policy, and Social Studies, Development Environment, Software Engineering

    4.6
    Rating, 4.6 out of 5 stars
    ·
    28 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Analyze Data in Azure ML Studio

    Skills you'll gain: Descriptive Statistics, Descriptive Analytics, Jupyter, Microsoft Azure, Statistical Visualization, Plot (Graphics), Model Training, Data Analysis, Statistics, Exploratory Data Analysis, Data Visualization Software, Correlation Analysis, Applied Machine Learning, Machine Learning Methods

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Deploy and Scale AI Models with Cloud Run

    Skills you'll gain: Google Cloud Platform, Model Deployment, Model Optimization, Serverless Computing, Cloud Deployment, Generative AI, Cloud Platforms, AI Integrations, Application Deployment, Cloud-Based Integration, Containerization, Scalability

    Beginner · Course · 1 - 4 Weeks

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

  • Interpretable machine learning applications: Part 3: Coursera
  • Machine Learning in Python: Analyze & Apply: EDUCBA
  • Decoding AI: A Deep Dive into AI Models and Predictions: University of Michigan
  • Machine Learning with Python & Statistics: EDUCBA
  • Interpretable Machine Learning Applications: Part 4: Coursera
  • 機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations: National Taiwan University
  • Machine Learning with R: Build, Analyze & Predict: EDUCBA
  • Decoding Large Language Models: Packt
  • Evaluating and Debugging Generative AI: DeepLearning.AI
  • Interpretable machine learning applications: Part 5: Coursera

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