- Convolutional Neural Networks
- Model Evaluation
- Recurrent Neural Networks (RNNs)
- Unsupervised Learning
- Performance Tuning
- Tensorflow
- Transfer Learning
- Reinforcement Learning
- Deep Learning
- Autoencoders
- Keras (Neural Network Library)
- Generative Adversarial Networks (GANs)
Deep Learning with Keras and Tensorflow
Completed by ADITYA M. KAKDE
June 23, 2020
23 hours (approximately)
ADITYA M. KAKDE'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
