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Explore the Keras Course Catalog
DeepLearning.AI
Skills you'll gain: Natural Language Processing, PyTorch (Machine Learning Library), Keras (Neural Network Library), Deep Learning, Tensorflow, Machine Learning Methods, Artificial Intelligence, Text Mining, Data Processing
Skills you'll gain: Tensorflow, Keras (Neural Network Library), Google Cloud Platform, Data Processing, Data Cleansing, Data Transformation, Scalability, Feature Engineering, Data Pipelines, MLOps (Machine Learning Operations), Deep Learning, Artificial Neural Networks, Applied Machine Learning, Machine Learning
Skills you'll gain: Tensorflow, Keras (Neural Network Library), Data Pipelines, Google Cloud Platform, Artificial Neural Networks, Data Transformation, Deep Learning, MLOps (Machine Learning Operations), Cloud Computing, Applied Machine Learning, Predictive Modeling, Machine Learning
Skills you'll gain: Tensorflow, Keras (Neural Network Library), Google Cloud Platform, Deep Learning, MLOps (Machine Learning Operations), Data Pipelines, Application Deployment, Cloud Computing, Applied Machine Learning, Artificial Neural Networks, Machine Learning, Data Transformation
Skills you'll gain: Tensorflow, Keras (Neural Network Library), Google Cloud Platform, Data Pipelines, MLOps (Machine Learning Operations), Application Deployment, Deep Learning, Data Processing, Artificial Neural Networks, Cloud Computing, Data Cleansing, Data Transformation, Machine Learning
Skills you'll gain: Tensorflow, Keras (Neural Network Library), Data Pipelines, Google Cloud Platform, Deep Learning, MLOps (Machine Learning Operations), Data Processing, Artificial Neural Networks, Applied Machine Learning, Scalability, Machine Learning, Data Transformation
Coursera Project Network
Skills you'll gain: PyTorch (Machine Learning Library), Heat Maps, Image Analysis, Deep Learning, Artificial Neural Networks, Computer Vision
DeepLearning.AI
Skills you'll gain: Deep Learning, Artificial Neural Networks, Tensorflow, Supervised Learning, Keras (Neural Network Library), Artificial Intelligence, Machine Learning, Python Programming, NumPy, Performance Tuning
Coursera Project Network
Skills you'll gain: PyTorch (Machine Learning Library), Artificial Neural Networks, Image Analysis, Deep Learning, Computer Vision
Skills you'll gain: PyTorch (Machine Learning Library), Artificial Neural Networks, Image Analysis, Deep Learning, Computer Vision, Classification And Regression Tree (CART), Predictive Modeling, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Machine Learning, Data Processing, Algorithms
DeepLearning.AI
Skills you'll gain: Natural Language Processing, Keras (Neural Network Library), Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Text Mining, Machine Learning
Skills you'll gain: Matplotlib, Deep Learning, Linear Algebra, Artificial Neural Networks, NumPy, Image Analysis, Keras (Neural Network Library), Data Visualization Software, Seaborn, Pandas (Python Package), Tensorflow, Machine Learning, Applied Machine Learning, Computer Vision, Supervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Data Analysis, PyTorch (Machine Learning Library), Jupyter, Python Programming
In summary, here are 10 of our most popular keras courses
- Natural Language Processing with Attention Models:Â DeepLearning.AI
- Build, Train and Deploy ML Models with Keras on Google Cloud - Italiano:Â Google Cloud
- Build, Train and Deploy ML Models with Keras on Google Cloud - í•œêµì–´: Google Cloud
- Build, Train and Deploy ML Models with Keras on Google Cloud - Français: Google Cloud
- Build, Train and Deploy ML Models with Keras on Google Cloud - Português Brasileiro: Google Cloud
- Build, Train and Deploy ML Models with Keras on Google Cloud - 日本語版: Google Cloud
- Deep Learning with PyTorch : GradCAM:Â Coursera Project Network
- Neural Networks and Deep Learning:Â DeepLearning.AI
- Deep Learning with PyTorch : Siamese Network:Â Coursera Project Network
- Building and Training Neural Networks with PyTorch:Â Packt
