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
Status: Free TrialUniversity of California, Santa Cruz
Skills you'll gain: Time Series Analysis and Forecasting, Forecasting, R Programming, Bayesian Statistics, Statistical Modeling, R (Software), Statistical Analysis, Statistical Inference, Regression Analysis, Data Analysis, Mathematical Modeling, Model Evaluation
Status: Free TrialCase Western Reserve University
Skills you'll gain: Geostatistics, Exploratory Data Analysis, Spatial Analysis, Descriptive Statistics, Box Plots, Statistical Modeling, Geospatial Information and Technology, R Programming, Plot (Graphics), Rmarkdown, Data Analysis, Data Cleansing, Statistical Methods, Simulations
Status: NewStatus: PreviewSkills you'll gain: Logistic Regression, Model Evaluation
Status: Free TrialEdureka
Skills you'll gain: Predictive Modeling, Predictive Analytics, Statistical Methods, Data Analysis, Applied Machine Learning, Business Analytics, Statistical Analysis, Machine Learning, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Data Preprocessing, Big Data, Python Programming, Data Manipulation, Pandas (Python Package), Logistic Regression, NumPy
Status: Free TrialJohns Hopkins University
Skills you'll gain: Regression Analysis, Linear Algebra, R Programming, Data Science, Probability Distribution, Statistical Modeling, Mathematical Modeling, Probability & Statistics, Applied Mathematics, Statistical Analysis, Statistical Inference
Status: Free TrialDeepLearning.AI
Skills you'll gain: Generative Adversarial Networks (GANs), Generative AI, Generative Model Architectures, PyTorch (Machine Learning Library), Model Evaluation, Responsible AI, Data Ethics, Machine Learning, Image Quality, Unsupervised Learning
Status: NewStatus: PreviewSkills you'll gain: SAS (Software), Statistical Modeling, Statistical Programming, Regression Analysis, Statistical Analysis, Model Evaluation, Statistical Methods, Probability Distribution, Data Manipulation
Status: Free TrialSkills you'll gain: Generative Adversarial Networks (GANs), Transfer Learning, Artificial Neural Networks, Keras (Neural Network Library), Image Analysis, Convolutional Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Data Preprocessing, Embeddings, Network Architecture, Matplotlib, Jupyter, NumPy
Status: Free TrialUniversity of Glasgow
Skills you'll gain: Autoencoders, Model Evaluation, Deep Learning, Healthcare 5.0, Recurrent Neural Networks (RNNs), Applied Machine Learning, Time Series Analysis and Forecasting, Machine Learning, Convolutional Neural Networks, Responsible AI, Electocardiography, Artificial Neural Networks
Status: NewStatus: PreviewSkills you'll gain: Model Evaluation, Data Preprocessing, Model Deployment, Risk Modeling, Logistic Regression, Statistical Analysis, Performance Metric
Status: Free TrialSkills you'll gain: Time Series Analysis and Forecasting, Recurrent Neural Networks (RNNs), SAS (Software), Forecasting, Regression Analysis, Applied Machine Learning, Statistical Analysis, Advanced Analytics, Predictive Modeling, Statistical Modeling, Bayesian Statistics, Model Evaluation
Status: Free TrialDuke University
Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, R (Software), Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Analysis, Descriptive Statistics
Searches related to probabilistic graphical models
In summary, here are 10 of our most popular probabilistic graphical models courses
- Bayesian Statistics: Time Series Analysis: University of California, Santa Cruz
- Using R for Geostatistical Geospatial Modeling : Case Western Reserve University
- SPSS: Apply & Interpret Logistic Regression Models: EDUCBA
- Predictive Modeling with Python : Edureka
- Advanced Linear Models for Data Science 2: Statistical Linear Models: Johns Hopkins University
- Build Better Generative Adversarial Networks (GANs): DeepLearning.AI
- SAS: Apply & Evaluate Poisson & Negative Binomial Models: EDUCBA
- Advanced Generative Adversarial Networks (GANs): Packt
- Explainable deep learning models for healthcare - CDSS 3: University of Glasgow
- Predictive Models: Build, Explore Data & Deploy: EDUCBA
