An open source library for deep learning end-to-end dialog systems and chatbots.

DeepPavlov tutorials

Introduction to DeepPavlov

Jupyter notebook slides

Install the library and understand a simple “Hello World!” Bot written in 7 lines of code. Experiment with basic pattern matching rule-based bot.

Data preparation in DeepPavlov

Jupyter notebook

Learn how to read and prepare data for trainable components.

Named Entity Recognition with DeepPavlov

Jupyter notebook slides video

Build a simple convolutional neural network to solve the named entity recognition task. Master data downloading, preprocessing and batching then train and score the model.

Task-oriented bot with DeepPavlov

Jupyter notebook slides video

Intro to DeepPavlov configs - a powerfull method to stack models. Study how to train 4 different task-oriented bots on DSTC2 dataset. These include (1) a basic bot, (2) a bot with a database of restaurants, (3) a bot with fasttext embeddings, (4) a bot with attention mechanism over input words.

Chit-chat bot with DeepPavlov

Jupyter notebook slides video

Implement in DeepPavlov sequence-to-sequence encoder-decoder model with attention mechanism and teacher forcing for chit-chat.