PyData Conference 2017
Code and Presentation for PyData Conference 2017
[Machine Learning Architectures]
We would talk about and implement some common machine learning architectures and building blocks which can be applied to a variety of use cases. The topics include Siamese networks, Triplet Networks, Skip connections, Batch Normalization and Dropout. We would use the Duplicate Question Dataset from Quora to demo these architectures.
- Download the dataset and GloVe vectors on the system.
- For the demo, we are using word vectors of dimensionality 100.
- Clone the repo.
- Install the dependencies using
sudo pip3 install -r requirements.txt
- Start with notebook on exploratory analysis.
- The path to the dataset and word vectors needs to be updated in the notebooks.