PyData Conference 2017
Code and Presentation for PyData Conference 2017
Topic
[Machine Learning Architectures]
Abstract
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.
Presentation
Dataset
Local Setup
- 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
cd notebook
jupyter notebook
- Start with notebook on exploratory analysis.
- The path to the dataset and word vectors needs to be updated in the notebooks.