Deep Learning for Free Text Generation - Rap Songs and Shakespeare

June 3, 2020 - Online

At this webinar we want to talk about deep learning networks, and specifically about recurrent neural networks! We’ll tackle the LSTM units and how to use them to generate free texts. The first talk by Kathrin Melcher will give an introduction to recurrent neural networks and LSTM units. The second talk by Rosaria Silipo will show a practical application for free text generation.

“Introduction to LSTM units in Deep Learning Architectures” by Kathrin Melcher (KNIME)
LSTM units in deep learning architectures are the state-of-the-art for sequence analysis. In this presentation we’ll find out what recurrent neural networks are, what LSTM units are and how they can remember or forget the past. We’ll also learn the difference between many to one, many to many, and one to many neural architectures.

“Yo! AI Generated Rap Songs” by Rosaria Silipo (KNIME)

Yo! This post is about generating free text
with a deep learning network
particularly it is about Brick X6,
Phey, cabe,
make you feel soom the way
I probably make
More money in six months,
Than what's in your papa's safe
Look like I robbed a bank …

You’d think I can rap. I cannot. The rap song up here was written by my deep learning LSTM-based, rap-trained recurrent neural network. We’ll show you how to prepare the data and build, train, and deploy a deep learning LSTM-based recurrent neural network for free text generation. Once built and trained on an appropriate training set, the network can be used to generate other kinds of free texts - for example Shakespearean text.

After the talks, Kathrin and Rosaria will be answering all your questions coming through on the Q&A Panel.


How do I join the workshop?

You’ll receive a zoom link with your registration confirmation. Make sure you have a stable internet connection!

Will I be able to ask questions?

Yes, we will have a Q&A and we'll do our best to answer these at the end of the workshop.

Where do I find the latest version of KNIME Analytics Platform?

Download the latest free, open source version of knime here: knime.com/download

What other resources will help me to get started in KNIME?