Using Keras to classify text with LSTMs and other ML techniques
Who is this presentation for?
- Machine learning engineers
Take a hands-on deep dive in building and improving a sentiment classifier on text data starting with scikit-learn and Naive Bayes and continuously improving the model.
Lukas Biewald explains Keras and applies word embeddings and convolutional neural networks (CNNs), and you’ll build various types of LSTMs and GRUs. You’ll be given a Jupyter hub instance set up with a cloud GPU to follow along.
- Familiarity with Python
- Experience with ML (not necessarily on text)
Materials or downloads needed in advance
- A WiFi-enabled laptop with the Chrome web browser installed
- Everything will be hosted on a Jupyter hub in a web browser to avoid installation problems. If you really want to configure things locally, install requirements.txt or follow the README.
What you'll learn
- Learn text handing with scikit-learn
- Understand how to build LSTMs and GRUs
- Get an introduction to Keras
Weights & Biases
Lukas Biewald is the founder of Weights & Biases. Previously, he was the founder of CrowdFlower, a machine learning data labeling company acquired by Appen. He was featured on Inc. magazine’s 30 under 30 list. Lukas holds a BS in mathematics and an MS in computer science from Stanford. He’s also an expert Go player.
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