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2. Transformers VS. SimpleTransformers
Brown edited this page Jun 21, 2020
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AI & Machine learning has developed quickly in the last several years. Deep learning techniques have provided some very powerful algorithms that can 'automatically' learn to identify patterns in unstructured data.
Below is high-level progression of neural networks:
| Type of Neural Network | Complexity | Application |
|---|---|---|
| Multi-layer perception (MLP) | Simple | Simple pattern recognition such as 'load default predictions' |
| Convolutional | Medium | Image classification, like classifying PNGs of dogs and cats |
| Recurrent neural network (RNN) | Medium | Predicting results based on a sequence of data, like text language translation |
| Transformers (the new kid on the block) | Crazy | Analyzing sequences of data and identifying relationships |
Transfomers
To implement standard transformer libraries is fairly involved and requires many lines of code. Instead Simple Transformers library can be used to get up and running quickly. Often in business we are under pressure to deliver something quickly, this library can be used to create a powerful transformer solution with only 3 lines of code: