- Artificial Intelligence and Machine Learning (AI/ML)
- Tensorflow
- Deep Learning
- Unsupervised Learning
- Artificial Neural Networks
- Performance Tuning
- Transfer Learning
- Reinforcement Learning
- Generative Adversarial Networks (GANs)
- Convolutional Neural Networks
- Autoencoders
- Recurrent Neural Networks (RNNs)
Deep Learning with Keras and Tensorflow
Completed by Dilip Kumar Bandaru
July 12, 2024
23 hours (approximately)
Dilip Kumar Bandaru'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
