Results for "ml explainability"
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
Duke University
Skills you'll gain: Fine-tuning, MLOps (Machine Learning Operations), Model Deployment, Cloud Deployment, Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Hugging Face, GitHub Copilot, Unit Testing, Responsible AI, DevOps, Cloud Computing, Python Programming, Machine Learning, GitHub, Big Data, Data Management, Data Analysis
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
Coursera
Skills you'll gain: MLOps (Machine Learning Operations), Data Pipelines, Model Evaluation, Systems Design, Transfer Learning, Data Preprocessing, Data Quality, Feature Engineering, Deep Learning, Python Programming, Data Validation, Scikit Learn (Machine Learning Library), Applied Machine Learning, Predictive Modeling, Software Engineering, Debugging, Supervised Learning, Git (Version Control System), Performance Metric, Statistical Analysis
Coursera
Skills you'll gain: Random Forest Algorithm, Model Evaluation, Feature Engineering, Model Training, Applied Machine Learning, Supervised Learning, Geospatial Mapping, Predictive Modeling, Image Analysis, Verification And Validation, Data Science, Environmental Engineering
Skills you'll gain: MLOps (Machine Learning Operations), Model Deployment, Model Training, Amazon Web Services, Apache Airflow, Data Pipelines, Apache Kafka, DevOps, CI/CD, Apache Spark, Pandas (Python Package), Deep Learning, Machine Learning, Data Governance, Supervised Learning, Flask (Web Framework), Grafana, Python Programming, Automation, Unsupervised Learning
What brings you to Coursera today?
Skills you'll gain: MLOps (Machine Learning Operations), Responsible AI, API Design, Multimodal Prompts, Data Preprocessing, Vision Transformer (ViT), Data Processing, Solution Architecture, Kubernetes, Apache Airflow, Transfer Learning, PyTorch (Machine Learning Library), Data Pipelines, CI/CD, Model Evaluation, Deep Learning, Natural Language Processing, Computer Vision, Docker (Software), Ethical Standards And Conduct
Microsoft
Skills you'll gain: Unsupervised Learning, Fine-tuning, Model Deployment, Generative AI, Large Language Modeling, Data Management, Generative Model Architectures, Natural Language Processing, MLOps (Machine Learning Operations), Supervised Learning, Microsoft Azure, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Generative Adversarial Networks (GANs), Infrastructure Architecture, LLM Application, Responsible AI, Data Infrastructure, Data Preprocessing, Model Optimization
Skills you'll gain: Verification And Validation, Sampling (Statistics), Statistical Machine Learning, Test Data, Machine Learning
Coursera
Skills you'll gain: Model Training, Predictive Modeling, Applied Machine Learning, Machine Learning Methods, Statistical Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Statistical Modeling, Technical Communication
Skills you'll gain: MLOps (Machine Learning Operations), Continuous Integration, Artificial Intelligence and Machine Learning (AI/ML), Service Level Agreement, Performance Stress Testing, Performance Measurement, Performance Analysis
Coursera
Skills you'll gain: Model Deployment, Unit Testing, MLOps (Machine Learning Operations), Kubernetes, Docker (Software), Containerization, Test Driven Development (TDD), Application Deployment, Continuous Integration, Software Testing, Model Training, CI/CD, Scalability, Scikit Learn (Machine Learning Library), Tensorflow, PyTorch (Machine Learning Library), Performance Tuning, Python Programming, Software Engineering, Git (Version Control System)
In summary, here are 10 of our most popular ml explainability courses
- Explainable AI (XAI):Â Duke University
- MLOps | Machine Learning Operations:Â Duke University
- Explain Black-Box Models:Â Coursera
- ML Model Training & Validation:Â Coursera
- Train ML Models:Â Coursera
- Hands-On MLOps Fundamentals for ML Engineers:Â KodeKloud
- Multimodal Intelligence - Vision, Audio & Language in Action:Â Coursera
- Microsoft AI & ML Engineering:Â Microsoft
- Validate and Explain Your ML Models:Â Coursera
- ML: Build, Train, Justify Models:Â Coursera
