Probabilistic Graphical Models Courses
Probabilistic Graphical Models courses can help you learn Bayesian networks, Markov random fields, and inference algorithms. You can build skills in modeling uncertainty, reasoning under uncertainty, and making predictions based on incomplete data. Many courses introduce tools like TensorFlow Probability and PyMC3, which are used for implementing these models and performing complex calculations, enabling you to apply your knowledge to real-world data analysis and machine learning tasks.
Popular Probabilistic Graphical Models Courses and Certifications
Skills you'll gain: Keras (Neural Network Library), Tensorflow, Applied Machine Learning, Deep Learning, Performance Tuning, Convolutional Neural Networks, Model Deployment, Python Programming
Status: FreeSkills you'll gain: Microsoft Azure, Unsupervised Learning, Applied Machine Learning, Predictive Analytics, Model Deployment, Data Transformation, Model Evaluation, Exploratory Data Analysis, Data Processing, Machine Learning Algorithms, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Cloud Computing, User Accounts
Status: Free TrialSkills you'll gain: Data Modeling, Database Design, Extract, Transform, Load, Data Warehousing, Data Pipelines, Business Intelligence, Data Mart, Database Management, Data Management, Process Optimization, Data Quality, Data Transformation, Performance Testing
Google Cloud
Skills you'll gain: Model Evaluation, Google Cloud Platform, Model Deployment, Cloud Computing, Generative AI
Status: Free TrialDeepLearning.AI
Skills you'll gain: Tensorflow, Transfer Learning, Deep Learning, Keras (Neural Network Library), Convolutional Neural Networks, Artificial Neural Networks, Model Evaluation
Status: PreviewSkills you'll gain: MLOps (Machine Learning Operations), Model Deployment, CI/CD, Continuous Deployment, Docker (Software), Kubernetes, Containerization, AI Workflows, Scalability, AI Orchestration, DevOps, Model Evaluation, Continuous Monitoring, Version Control
Status: Free TrialSkills you'll gain: PyTorch (Machine Learning Library), Large Language Modeling, Embeddings, Generative AI, Natural Language Processing, Transfer Learning, Recurrent Neural Networks (RNNs), Data Ethics, Artificial Neural Networks, Classification Algorithms, Model Evaluation, Data Preprocessing, Feature Engineering
Status: NewSkills you'll gain: Generative AI
Status: PreviewSkills you'll gain: LLM Application, Large Language Modeling, Google Gemini, Generative AI, Prompt Engineering
Status: Free TrialSkills you'll gain: 3D Assets, Computer Graphics, Technical Design, Visualization (Computer Graphics), Image Quality, Prototyping, Animations, Animation and Game Design, Color Theory, Design Elements And Principles
Status: PreviewSkills you'll gain: Prompt Engineering, Large Language Modeling, LLM Application, Google Gemini, Generative AI
Status: PreviewSkills you'll gain: Natural Language Processing, Large Language Modeling, Transfer Learning, Vision Transformer (ViT), Generative Model Architectures
Searches related to probabilistic graphical models
In summary, here are 10 of our most popular probabilistic graphical models courses
- Optimize TensorFlow Models For Deployment with TensorRT: Coursera
- Develop Clustering Models with Azure ML Designer: Microsoft
- The Path to Insights: Data Models and Pipelines: Google
- Explore and Evaluate Models using Model Garden: Google Cloud
- Custom Models, Layers, and Loss Functions with TensorFlow: DeepLearning.AI
- Operationalizing ML Models: MLOps for Scalable AI: Coursera
- Gen AI Foundational Models for NLP & Language Understanding: IBM
- Train Large Language Models Faster - Parallelism Deep Dive: Packt
- Introduction to Large Language Models - Português Brasileiro: Google Cloud
- Blender 4 Creator Course Stylized 3D Models: Packt
