- Keras (Neural Network Library)
- Transfer Learning
- Model Evaluation
- Performance Tuning
- Deep Learning
- Tensorflow
- Artificial Intelligence and Machine Learning (AI/ML)
- Autoencoders
- Reinforcement Learning
- Convolutional Neural Networks
- Recurrent Neural Networks (RNNs)
- Generative Adversarial Networks (GANs)
Deep Learning with Keras and Tensorflow
Completed by Sarah-Beth Amos
February 12, 2020
23 hours (approximately)
Sarah-Beth Amos's account is verified. Coursera certifies their successful completion of Deep Learning with Keras and Tensorflow
What you will learn
Create custom layers and models in Keras and integrate Keras with TensorFlow 2.x
Develop advanced convolutional neural networks (CNNs) using Keras
Develop Transformer models for sequential data and time series prediction
Explain key concepts of Unsupervised learning in Keras, Deep Q-networks (DQNs), and reinforcement learning
Skills you will gain
