Deep learning (Coursera)

Here, I will introduce foundations of Deep Learning to understand how to build neural networks, and how to lead successful machine learning projects. Also, I will explain about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. Furthermore, I will show case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing.

• Machine learning vs. Deep learning
• Batch normalization
• Recurrent neural network
• Long Short-Term Memory models (LSTM)
• Attention mechanism

Reference

• Coursera