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: Jupyter, Plot (Graphics), Model Evaluation, Microsoft Azure, Machine Learning Algorithms, Applied Machine Learning, Data Visualization, Regression Analysis
Status: Free TrialSkills you'll gain: Prompt Engineering, LLM Application, Model Deployment, Responsible AI, Application Deployment, Application Development, Hugging Face, Data Ethics, Generative AI, AI Security, Application Security, Continuous Monitoring
Status: Free TrialSkills you'll gain: Large Language Modeling, Generative AI, Model Deployment, Natural Language Processing, Prompt Engineering, Deep Learning, MLOps (Machine Learning Operations), Cloud Deployment, Model Evaluation, Continuous Monitoring, Data Cleansing, Machine Learning
Status: Free TrialSkills you'll gain: Model Evaluation, Generative AI, LLM Application, Prompt Engineering, Training Programs, Large Language Modeling, Applied Machine Learning, Open Source Technology, Benchmarking, Artificial Neural Networks
Status: NewStatus: Free TrialSkills you'll gain: Model Evaluation, Convolutional Neural Networks, Keras (Neural Network Library), Image Analysis, Data Preprocessing, Deep Learning, Computer Vision, Tensorflow, Python Programming, Cloud Computing, Development Environment
Status: NewStatus: Free TrialSkills you'll gain: PyTorch (Machine Learning Library), Transfer Learning, Natural Language Processing, Large Language Modeling, Generative Model Architectures, Embeddings
Status: NewStatus: Free TrialSkills you'll gain: Continuous Improvement Process, Process Improvement, Risk Management, Performance Measurement, Quality Management, Process Analysis, Performance Management, Project Management, Process Optimization, Verification And Validation, Requirements Analysis, Project Planning, Root Cause Analysis
Status: NewStatus: Free TrialSkills you'll gain: Vision Transformer (ViT), Model Deployment, Transfer Learning, Hugging Face, MLOps (Machine Learning Operations), Cloud Deployment, Large Language Modeling, Computer Vision, Image Analysis, Natural Language Processing, Application Deployment
Status: PreviewDuke University
Skills you'll gain: LLM Application, Large Language Modeling, Model Deployment, Embeddings, Application Programming Interface (API), Restful API, Natural Language Processing, Command-Line Interface, Machine Learning
Status: Free TrialSkills you'll gain: Recurrent Neural Networks (RNNs), Embeddings, Deep Learning, Convolutional Neural Networks, Artificial Neural Networks, Python Programming, Classification Algorithms, Data Preprocessing, Model Evaluation
Status: NewStatus: Free TrialSkills you'll gain: Prompt Engineering, Large Language Modeling, Natural Language Processing, Generative AI, Transfer Learning, Embeddings, Data Preprocessing, Model Evaluation
Status: Free TrialJohns Hopkins University
Skills you'll gain: Regression Analysis, Statistical Modeling, R Programming, Linear Algebra, Data Science, Mathematical Modeling, Data Modeling, Statistics, Statistical Analysis, Applied Mathematics, General Mathematics, Derivatives
Searches related to probabilistic graphical models
In summary, here are 10 of our most popular probabilistic graphical models courses
- Compare Models with Experiments in Azure ML Studio: Coursera
- Building Production-Ready Apps with Large Language Models: Coursera
- NVIDIA: Large Language Models and Generative AI Deployment: Whizlabs
- H2O ai Large Language Models (LLMs) - Level 3: H2O.ai
- Master CNNs with Python: Build, Train & Evaluate Models: EDUCBA
- Introduction to Transformer Models for NLP: Unit 1: Pearson
- Master Quality Models with CMMI: Analyze, Apply & Improve: EDUCBA
- Introduction to Transformer Models for NLP: Unit 3: Pearson
- Beginning Llamafile for Local Large Language Models (LLMs): Duke University
- Natural Language Processing - Deep Learning Models in Python: Packt
