Results for "probabilistic+neural+networks"
Johns Hopkins University
Skills you'll gain: Responsible AI, Autoencoders, Model Training, Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Data Ethics, Model Optimization, Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Generative Adversarial Networks (GANs), Machine Learning Algorithms, Model Deployment, Generative Model Architectures, Debugging, Machine Learning Methods, Artificial Intelligence, Image Analysis, Unsupervised Learning
Dartmouth College
Skills you'll gain: Supervised Learning, Bayesian Network, Logistic Regression, Artificial Neural Networks, Machine Learning Methods, Statistical Modeling, Predictive Modeling, Model Evaluation, Convolutional Neural Networks, Statistical Machine Learning, Probability & Statistics, Bayesian Statistics, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Statistical Methods, Artificial Intelligence, Regression Analysis, Statistical Inference
Skills you'll gain: Computer Vision, Image Analysis, Model Evaluation, Convolutional Neural Networks, Model Optimization, Artificial Neural Networks, Model Training, Machine Learning Methods, PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Transfer Learning, Machine Learning, Recurrent Neural Networks (RNNs), Artificial Intelligence, NumPy, Python Programming, Matplotlib, Data Visualization, Data Science
Skills you'll gain: Descriptive Statistics, A/B Testing, Classification And Regression Tree (CART), Dashboard, Dashboard Creation, Model Evaluation, Model Deployment, Data-Driven Decision-Making, Risk Analysis, Histogram, Statistical Inference, Descriptive Analytics, Simulations, Predictive Modeling, Regression Analysis, Data Visualization, MLOps (Machine Learning Operations), Decision Making, Decision Tree Learning, Keras (Neural Network Library)
Stanford University
Skills you'll gain: Bayesian Network, Applied Machine Learning, Decision Intelligence, Bayesian Statistics, Graph Theory, Machine Learning Algorithms, Probability Distribution, Network Model, Statistical Modeling, Machine Learning Methods, Markov Model, Decision Support Systems, Machine Learning, Unsupervised Learning, Probability & Statistics, Network Analysis, Statistical Inference, Model Training, Statistical Machine Learning, Model Optimization
Skills you'll gain: Keras (Neural Network Library), Deep Learning, Transfer Learning, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Model Optimization, Machine Learning Methods, Image Analysis, Applied Machine Learning, Autoencoders, Model Training, Regression Analysis, Network Architecture, Natural Language Processing, Machine Learning
What brings you to Coursera today?
Skills you'll gain: PyTorch (Machine Learning Library), Deep Learning, Convolutional Neural Networks, Model Training, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Model Optimization, Image Analysis, Model Evaluation, Classification Algorithms
Skills you'll gain: Model Evaluation, Keras (Neural Network Library), Software Documentation, Technical Documentation, Artificial Neural Networks, PyTorch (Machine Learning Library), Model Training, Deep Learning, Model Optimization, Applied Machine Learning, Network Architecture
Skills you'll gain: Bayesian Network, Bayesian Statistics, Network Model, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Markov Model, Statistical Modeling, Statistical Inference, Graph Theory, Probability & Statistics, Sampling (Statistics), Algorithms
Imperial College London
Skills you'll gain: Generative AI, Tensorflow, Autoencoders, Generative Model Architectures, Bayesian Network, Deep Learning, Image Analysis, Bayesian Statistics, Model Optimization, Probability Distribution, Model Training, Sampling (Statistics), Data Transformation
Skills you'll gain: PyTorch (Machine Learning Library), Logistic Regression, Applied Machine Learning, Predictive Modeling, Classification Algorithms, Predictive Analytics, Model Optimization, Tensorflow, Machine Learning, Model Training, Supervised Learning, Deep Learning, Regression Analysis, Model Evaluation, Statistical Methods, Data Preprocessing, Artificial Neural Networks, Data Processing, Probability & Statistics
Skills you'll gain: Model Deployment, Model Training, Deep Learning, PyTorch (Machine Learning Library), Scalability, Docker (Software), Application Deployment, Containerization, Model Evaluation, Artificial Neural Networks, Tensorflow, Configuration Management
In summary, here are 10 of our most popular probabilistic+neural+networks courses
- Foundations of Neural Networks:Â Johns Hopkins University
- Practical Machine Learning: Foundations to Neural Networks:Â Dartmouth College
- Neural Networks and Computer Vision Foundations:Â Edureka
- Statistical Inference & Predictive Modeling Foundations:Â Coursera
- Probabilistic Graphical Models:Â Stanford University
- Introduction to Deep Learning & Neural Networks with Keras:Â IBM
- Deep Learning with PyTorch:Â IBM
- Start Neural Networks Advanced Model Architectures:Â Coursera
- Probabilistic Graphical Models: A Compact Introduction:Â Coursera
- Probabilistic Deep Learning with TensorFlow 2:Â Imperial College London
