Results for "tensorflow+probability"
DeepLearning.AI
Skills you'll gain: Tensorflow, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Computer Vision, Model Evaluation, Transfer Learning, Image Analysis, Keras (Neural Network Library), Natural Language Processing, Time Series Analysis and Forecasting, Deep Learning, Embeddings, Artificial Neural Networks, Generative AI, Applied Machine Learning, Classification Algorithms, Predictive Modeling, Data Preprocessing, Forecasting, Machine Learning
Imperial College London
Skills you'll gain: Tensorflow, Recurrent Neural Networks (RNNs), Autoencoders, Generative Model Architectures, Data Pipelines, Keras (Neural Network Library), Model Evaluation, Deep Learning, Image Analysis, Transfer Learning, Convolutional Neural Networks, Applied Machine Learning, Bayesian Statistics, Supervised Learning, Natural Language Processing, Computer Vision, Model Deployment, Artificial Neural Networks, Data Preprocessing, Probability Distribution
Stanford University
Skills you'll gain: Bayesian Network, Applied Machine Learning, Graph Theory, Machine Learning Algorithms, Probability Distribution, Network Model, Statistical Modeling, Markov Model, Decision Support Systems, Machine Learning, Probability & Statistics, Network Analysis, Classification Algorithms, Machine Learning Methods, Statistical Inference, Sampling (Statistics), Statistical Methods, Algorithms, Regression Analysis, Computational Thinking
University of Colorado Boulder
Skills you'll gain: Probability, Statistical Inference, Estimation, Probability & Statistics, Statistical Methods, Probability Distribution, Statistics, Markov Model, Data Literacy, Statistical Analysis, Sampling (Statistics), Applied Mathematics, Artificial Intelligence, Generative AI, Data Analysis, Data Science, Theoretical Computer Science, Machine Learning Algorithms, Mathematical Theory & Analysis
DeepLearning.AI
Skills you'll gain: Generative Adversarial Networks (GANs), Autoencoders, Generative AI, Tensorflow, Computer Vision, Image Analysis, Transfer Learning, Convolutional Neural Networks, Generative Model Architectures, Deep Learning, Keras (Neural Network Library), Artificial Neural Networks, Classification Algorithms, Model Evaluation, Distributed Computing, Visualization (Computer Graphics), Performance Tuning, Network Architecture
Imperial 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)
What brings you to Coursera today?
Johns Hopkins University
Skills you'll gain: R Programming, Statistical Analysis, Statistical Programming, Data Analysis, Probability, Probability Distribution, Applied Machine Learning, Probability & Statistics, Applied Mathematics, Data Science, Computational Thinking, Simulations
University of Zurich
Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Statistics, Descriptive Statistics, Applied Mathematics, Risk Analysis, Finance
Skills you'll gain: PyTorch (Machine Learning Library), Transfer Learning, Model Evaluation, Vision Transformer (ViT), Keras (Neural Network Library), Deep Learning, Convolutional Neural Networks, Reinforcement Learning, Autoencoders, Unsupervised Learning, Tensorflow, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Statistical Methods, Logistic Regression, Machine Learning Methods, Image Analysis, Data Preprocessing, Model Deployment
DeepLearning.AI
Skills you'll gain: Model Deployment, Extract, Transform, Load, Federated Learning, Data Pipelines, Image Analysis, Data Import/Export, Tensorflow, Transfer Learning, Convolutional Neural Networks, iOS Development, Android Development, Data Preprocessing, Data Processing, Computer Vision, Swift Programming, MLOps (Machine Learning Operations), Model Evaluation, Mobile Development, Javascript, Machine Learning
Skills you'll gain: Descriptive Statistics, A/B Testing, Classification And Regression Tree (CART), Dashboard, Model Evaluation, Model Deployment, Data-Driven Decision-Making, Risk Analysis, Histogram, Statistical Inference, Strategic Decision-Making, Data Presentation, Predictive Modeling, Statistical Hypothesis Testing, Risk Mitigation, Regression Analysis, Data Visualization, MLOps (Machine Learning Operations), Decision Tree Learning, Keras (Neural Network Library)
University of London
Skills you'll gain: Descriptive Statistics, Statistics, Probability & Statistics, Statistical Hypothesis Testing, Data Visualization, Data-Driven Decision-Making, Statistical Modeling, Data Analysis, Probability, Probability Distribution, Sampling (Statistics), Risk Modeling, Statistical Inference, Mathematical Modeling
In summary, here are 10 of our most popular tensorflow+probability courses
- DeepLearning.AI TensorFlow Developer:Â DeepLearning.AI
- TensorFlow 2 for Deep Learning:Â Imperial College London
- Probabilistic Graphical Models:Â Stanford University
- Foundations of Probability and Statistics:Â University of Colorado Boulder
- TensorFlow: Advanced Techniques:Â DeepLearning.AI
- Probabilistic Deep Learning with TensorFlow 2:Â Imperial College London
- Foundations of Probability and Random Variables:Â Johns Hopkins University
- An Intuitive Introduction to Probability:Â University of Zurich
- IBM Deep Learning with PyTorch, Keras and Tensorflow:Â IBM
- TensorFlow: Data and Deployment:Â DeepLearning.AI
