Understanding and Implementing Recurrent Neural Networks Using Python

Explore the intricacies of Recurrent Neural Networks (RNNs) in this 40-minute conference talk from EuroPython 2018. Delve into the world of deep learning, starting with an introduction to Artificial Neural Networks before focusing on the unique properties of RNNs. Compare feedforward and feedback networks, and gain hands-on experience implementing RNNs using Python and Keras. Understand key concepts such as Backpropagation Through Time (BPTT) and the Vanishing Gradient Problem. Advance your knowledge with an exploration of more sophisticated RNN variants like Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTMs). Perfect for those interested in pattern recognition in sequential data, including numerical time series, images, text, speech, and genome sequences.

Anmol Krishan Sachdeva - Understanding and Implementing Recurrent Neural Networks using Python