Results for "probabilistic+neural+network"
Status: Free TrialStanford University
Skills you'll gain: Bayesian Network, Applied Machine Learning, Graph Theory, Machine Learning Algorithms, Probability Distribution, Network Model, Bayesian Statistics, Statistical Modeling, Markov Model, Decision Support Systems, Machine Learning, Probability & Statistics, Network Analysis, Machine Learning Methods, Statistical Inference, Sampling (Statistics), Statistical Methods, Algorithms, Model Evaluation, Computational Thinking
Status: Free TrialImperial College London
Skills you'll gain: Tensorflow, Autoencoders, Generative Model Architectures, Deep Learning, Applied Machine Learning, Image Analysis, Bayesian Statistics, Probability Distribution, Unsupervised Learning, Sampling (Statistics)
Status: NewStatus: Free Trial
Status: Free TrialJohns Hopkins University
Skills you'll gain: Responsible AI, Autoencoders, Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Data Ethics, Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Generative Adversarial Networks (GANs), Machine Learning Algorithms, Model Deployment, Debugging, Artificial Intelligence, Image Analysis, Unsupervised Learning, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Computer Vision
Status: Free TrialSkills you'll gain: PyTorch (Machine Learning Library), Convolutional Neural Networks, Deep Learning, Artificial Neural Networks, Applied Machine Learning, Supervised Learning, Classification Algorithms, Model Evaluation
Status: Free TrialSkills you'll gain: PyTorch (Machine Learning Library), Statistical Methods, Logistic Regression, Tensorflow, Artificial Neural Networks, Probability & Statistics, Regression Analysis, Model Evaluation, Data Preprocessing
What brings you to Coursera today?
Status: NewStatus: Free TrialSkills you'll gain: Applied Machine Learning, Analysis, Performance Analysis
Status: Free TrialStanford University
Skills you'll gain: Bayesian Network, Applied Machine Learning, Machine Learning Algorithms, Bayesian Statistics, Markov Model, Machine Learning, Statistical Modeling, Probability Distribution, Statistical Methods, Algorithms, Model Evaluation
Status: NewStatus: Free TrialSkills you'll gain: Convolutional Neural Networks, Model Evaluation, Keras (Neural Network Library), Image Analysis, Deep Learning, Applied Machine Learning, Computer Vision, Dimensionality Reduction, PyTorch (Machine Learning Library), Tensorflow, Machine Learning Methods, Data Preprocessing, Performance Tuning, Artificial Intelligence
Status: NewStatus: Free TrialSkills you'll gain: Recurrent Neural Networks (RNNs), Transfer Learning, Convolutional Neural Networks, Deep Learning, Keras (Neural Network Library), Tensorflow, Artificial Neural Networks, PyTorch (Machine Learning Library), Image Analysis, Natural Language Processing, Computer Vision, Model Evaluation, Data Preprocessing
Status: NewStatus: Free TrialSkills you'll gain: Model Evaluation, Convolutional Neural Networks, Data Preprocessing, Keras (Neural Network Library), Image Analysis, Deep Learning, Tensorflow, Computer Vision, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Data Manipulation, Data Transformation, Financial Forecasting, Data Visualization, Time Series Analysis and Forecasting, Exploratory Data Analysis, Python Programming, Customer Analysis, Applied Machine Learning, Cloud Computing
- Status: Free Trial
Stanford University
Skills you'll gain: Bayesian Network, Graph Theory, Probability Distribution, Network Model, Statistical Modeling, Markov Model, Decision Support Systems, Probability & Statistics, Network Analysis, Machine Learning Algorithms
What brings you to Coursera today?
In summary, here are 10 of our most popular probabilistic+neural+network courses
- Probabilistic Graphical Models:Â Stanford University
- Probabilistic Deep Learning with TensorFlow 2:Â Imperial College London
- Design and Build Custom Neural Networks:Â Coursera
- Foundations of Neural Networks:Â Johns Hopkins University
- Deep Learning with PyTorch:Â IBM
- Introduction to Neural Networks and PyTorch:Â IBM
- Debug Neural Networks: Analyze Training Dynamics:Â Coursera
- Probabilistic Graphical Models 3: Learning:Â Stanford University
- Foundations of Model Optimization and Deep Learning:Â Packt
- Deep Learning & Modern AI Architectures:Â Packt
