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Binary Text Classification | The Problem | Dan Brown v Oscar Wilde (Neural Nets for DH 11a)
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Classroom Contents
Neural Networks for Digital Humanities
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- 1 An Easy Introduction to Machine Learning
- 2 Intro to Deep Learning (Neural Networks for DH 02)
- 3 What are Models and Layers (Neural Networks for DH 03)
- 4 How Training Works (Neural Networks for DH 04)
- 5 Validation, Testing, and Loss (Neural Networks for DH 05)
- 6 What is Prediction (Neural Networks for DH 06)
- 7 Types of Neural Networks (Neural Networks for DH 07)
- 8 What is TensorFlow (Neural Networks for DH 08)
- 9 What is Keras (Neural Networks for DH 09)
- 10 Shallow Neural Networks SNNs (Neural Networks for DH 10)
- 11 Binary Text Classification | The Problem | Dan Brown v Oscar Wilde (Neural Nets for DH 11a)
- 12 Preparing and Labeling Data for Binary Text Classification (Neural Networks for DH 11b)
- 13 Creating and Training a Binary Text Classification Model in Keras (Neural Networks for DH 11c)
- 14 How to Save, Load, and Test Models in Keras and TensorFlow (Neural Networks for DH 11d)
