Results for "deep+learning+methods"
Coursera
Skills you'll gain: Model Deployment, PyTorch (Machine Learning Library), Vision Transformer (ViT), Model Evaluation, Transfer Learning, MLOps (Machine Learning Operations), Natural Language Processing, Debugging, Containerization, Kubernetes, Docker (Software), Distributed Computing, Performance Tuning, Applied Machine Learning, Dataflow, Tensorflow, Deep Learning, Cloud Computing, Data Pipelines, Computer Vision
DeepLearning.AI
Skills you'll gain: Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Computer Vision, Transfer Learning, Deep Learning, Image Analysis, Hugging Face, Natural Language Processing, Artificial Neural Networks, Tensorflow, Embeddings, Supervised Learning, Keras (Neural Network Library), Applied Machine Learning, Machine Learning, MLOps (Machine Learning Operations), Debugging, Performance Tuning, PyTorch (Machine Learning Library), Data Preprocessing
DeepLearning.AI
Skills you'll gain: PyTorch (Machine Learning Library), Model Deployment, Convolutional Neural Networks, Transfer Learning, Data Quality, Generative AI, Deep Learning, Image Analysis, MLOps (Machine Learning Operations), Data Pipelines, Embeddings, Applied Machine Learning, Artificial Neural Networks, Model Evaluation, Software Visualization, Computer Vision, Data Preprocessing, Natural Language Processing, Machine Learning
Status: Top AI ProgramDeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Data Preprocessing, Machine Learning, Machine Learning Methods
Skills you'll gain: Model Deployment, Transfer Learning, Keras (Neural Network Library), Deep Learning, Applied Machine Learning, Tensorflow, PyTorch (Machine Learning Library), Convolutional Neural Networks, Artificial Neural Networks, Machine Learning Methods, Application Frameworks, Model Evaluation, Performance Tuning
Skills you'll gain: PyTorch (Machine Learning Library), Convolutional Neural Networks, Deep Learning, Artificial Neural Networks, Applied Machine Learning, Supervised Learning, Classification Algorithms, Model Evaluation
What brings you to Coursera today?
Johns 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
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, Image Analysis, Data Preprocessing, Model Deployment, Computer Vision
Skills 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
MathWorks
Skills you'll gain: Model Evaluation, Computer Vision, Model Deployment, Anomaly Detection, Convolutional Neural Networks, Image Analysis, Transfer Learning, Matlab, Deep Learning, Artificial Neural Networks, Applied Machine Learning, PyTorch (Machine Learning Library), Data Preprocessing, Classification Algorithms, Data Visualization, Data Synthesis, Performance Tuning, Data Analysis
Skills you'll gain: Recurrent Neural Networks (RNNs), Artificial Neural Networks, Deep Learning, Matplotlib, Convolutional Neural Networks, Linear Algebra, Image Analysis, Data Visualization, NumPy, Machine Learning Algorithms, Keras (Neural Network Library), Pandas (Python Package), Seaborn, Artificial Intelligence and Machine Learning (AI/ML), Data Science, Applied Machine Learning, Tensorflow, Data Analysis, Artificial Intelligence, Machine Learning
Skills you'll gain: Recurrent Neural Networks (RNNs), Transfer Learning, Tensorflow, Artificial Neural Networks, Embeddings, Keras (Neural Network Library), Deep Learning, Time Series Analysis and Forecasting, Image Analysis, Classification Algorithms, Convolutional Neural Networks, Natural Language Processing, Computer Vision, Forecasting, Supervised Learning, Machine Learning Algorithms, Machine Learning, Predictive Analytics, Model Evaluation, Predictive Modeling
In summary, here are 10 of our most popular deep+learning+methods courses
- Deep Learning Engineering: Coursera
- Deep Learning: DeepLearning.AI
- PyTorch for Deep Learning: DeepLearning.AI
- Mathematics for Machine Learning and Data Science: DeepLearning.AI
- Deep Learning and Advanced Techniques: Packt
- Deep Learning with PyTorch: IBM
- Foundations of Neural Networks: Johns Hopkins University
- IBM Deep Learning with PyTorch, Keras and Tensorflow: IBM
- Foundations of Model Optimization and Deep Learning: Packt
- Deep Learning for Computer Vision: MathWorks
