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
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, Generative AI Agents, Data Preprocessing, Model Optimization
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: 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
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
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
What brings you to Coursera today?
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
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), 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
Skills you'll gain: Tensorflow, Model Optimization, Keras (Neural Network Library), Model Training, MLOps (Machine Learning Operations), Data Pipelines, Performance Tuning, Data Preprocessing
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
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Microservices, Containerization, Application Deployment, Service Level, Debugging, Unit Testing, Software Testing, System Monitoring, Continuous Deployment, Docker (Software), Software Architecture, Kubernetes, Software Design, Restful API, Systems Architecture, Cloud Computing Architecture, Application Performance Management, Continuous Monitoring
Skills you'll gain: Verification And Validation, Sampling (Statistics), Statistical Machine Learning, Test Data, Machine Learning
In summary, here are 10 of our most popular ml explainability courses
- Explainable AI (XAI):Â Duke University
- Microsoft AI & ML Engineering:Â Microsoft
- Explain Black-Box Models:Â Coursera
- Train ML Models:Â Coursera
- MLOps | Machine Learning Operations:Â Duke University
- Multimodal Intelligence - Vision, Audio & Language in Action:Â Coursera
- ML Model Training & Validation:Â Coursera
- Hands-On MLOps Fundamentals for ML Engineers:Â KodeKloud
- Build & Optimize TensorFlow ML Workflows:Â Coursera
- Responsible AI, Explainability & Deployment:Â Coursera
