Results for "model interpretability"
Duke University
Skills you'll gain: Responsible AI, Large Language Modeling, Data Ethics, Decision Tree Learning, Regression Analysis, Generative AI, Artificial Intelligence, AI literacy, Decision Intelligence, Applied Machine Learning, Generative Model Architectures, Statistical Modeling, Python Programming, Machine Learning, Model Evaluation, Embeddings, Image Analysis, Machine Learning Methods, Scientific Visualization, Deep Learning
Skills you'll gain: Decision Intelligence, Responsible AI, Apache Kafka, Data Ethics, Operations Research, Data Pipelines, Model Deployment, Apache Spark, Real Time Data, Revenue Management, Market Dynamics, Supply Chain Planning, Supply Chain, Logistics, Compliance Management, Information Privacy, People Analytics, Regulatory Compliance, General Data Protection Regulation (GDPR), Python Programming
Coursera
Skills you'll gain: Stakeholder Communications, Stakeholder Engagement, Data Storytelling, Stakeholder Management, Stakeholder Analysis, Data Presentation, Data-Driven Decision-Making, Business Communication, Model Evaluation, Responsible AI
Pragmatic AI Labs
Skills you'll gain: Responsible AI, Model Evaluation, AI Integrations, Model Deployment, GitHub, Application Programming Interface (API), AI Enablement, Generative AI, Development Environment, API Design, LLM Application, Cloud Development, Microsoft Azure, Prompt Engineering, Capacity Management, Scalability, Authentications, Data Validation
Skills you'll gain: Classification And Regression Tree (CART), Decision Tree Learning, Large Language Modeling, Retrieval-Augmented Generation, LLM Application, Data Analysis, Applied Machine Learning, Keras (Neural Network Library), Machine Learning Methods, Model Evaluation, Model Training, Fine-tuning, Model Deployment, Generative AI, Text Mining, Prompt Engineering, Deep Learning, Random Forest Algorithm, Machine Learning, MLOps (Machine Learning Operations)
Skills you'll gain: Bayesian Network, Bayesian Statistics, Network Model, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Markov Model, Statistical Modeling, Statistical Inference, Graph Theory, Probability & Statistics, Sampling (Statistics), Algorithms
What brings you to Coursera today?
Skills you'll gain: Model Evaluation, Model Training, MLOps (Machine Learning Operations), System Monitoring, Continuous Monitoring, Model Deployment, Verification And Validation, Performance Metric, A/B Testing, Statistical Methods, Failure Analysis, Statistical Hypothesis Testing, Applied Machine Learning, Statistical Analysis, Scikit Learn (Machine Learning Library), Benchmarking
Stanford University
Skills you'll gain: Bayesian Network, Applied Machine Learning, Decision Intelligence, Bayesian Statistics, Graph Theory, Machine Learning Algorithms, Probability Distribution, Network Model, Statistical Modeling, Machine Learning Methods, Markov Model, Decision Support Systems, Machine Learning, Unsupervised Learning, Probability & Statistics, Network Analysis, Statistical Inference, Model Training, Statistical Machine Learning, Model Optimization
Skills you'll gain: Model Evaluation, MLOps (Machine Learning Operations), AI Workflows, Applied Machine Learning, Model Optimization, Data Pipelines, Responsible AI, Statistical Modeling
Skills you'll gain: Regression Analysis, Predictive Modeling, Model Evaluation, Statistical Modeling, Predictive Analytics, R Programming, Financial Forecasting, Statistical Methods, Model Training, Data Validation, Verification And Validation, Plot (Graphics), Performance Metric
Skills you'll gain: Machine Learning Methods, Predictive Modeling, Model Training, Statistical Machine Learning, Machine Learning Software, Model Optimization, Performance Analysis, Performance Metric, Performance Improvement
Skills you'll gain: Model Evaluation, Fine-tuning, Model Optimization, Hugging Face, Model Deployment, Model Training, Transfer Learning, Natural Language Processing, MLOps (Machine Learning Operations), Large Language Modeling, Performance Tuning, Generative Model Architectures, Application Deployment, Data Preprocessing, Data Pipelines, Embeddings, Version Control, Git (Version Control System)
In summary, here are 10 of our most popular model interpretability courses
- Explainable AI (XAI): Duke University
- Responsible AI, Explainability & Deployment: Coursera
- Explain Black-Box Models: Coursera
- GitHub: Evaluating and Integrating AI Models: Pragmatic AI Labs
- Advanced Model Architectures & Language AI: Coursera
- Probabilistic Graphical Models: A Compact Introduction: Coursera
- Training, Evaluating, and Monitoring Machine Learning Models: Coursera
- Probabilistic Graphical Models: Stanford University
- Calibrate and Serve Confident AI Predictions: Coursera
- Predict and Validate Regression Models in R: Coursera
