I use an IPython notebook with instructions and some code prepared.

• I use Python 3 and Tensorflow 1.0. And it work with many libraries, e.g. NLTK, Scikit-learn, Gensim, Tensorflow, etc.

Use Google Colab where you can install or import all necessary libraries. Instructions on how to run code on Colab are provided in Here.

In this project learn how to predict tags for posts from StackOverflow. To solve this task I used multilable classification approach.

• Numpy: a package for scientific computing.
• Pandas: a library providing high-performance, easy-to-use data structures and data analysis tools for the Python
• scikit-learn: a tool for data mining and data analysis
• NLTK: a platform to work with natural language

In this project, will use a recurrent neural network to solve Named Entity Recognition(NER) problem. NER is a common task in natural language processing systems. It serves for extraction such entities from the text as persons, organizations, locations, etc.

• Tensorflow: In this, will use Tensorflow 1.15.0.

!pip install tensorflow==1.15.0

• Numpy

In this task, learn how to calculate a similarity for pieces of text. Using this approach you will know how to find duplicate questions from StackOverflow.

• StarSpace
• Gensim
• Numpy
• scikit-learn
• NLTK

We can see how to use neural networks to solve sequence-to-sequence prediction tasks.Seq2seq models are very popular these days because they achieve great result in Machine Translation, Text Summarization, Conversational Modeling and more.

combine everything before tasks to construct a dialogue chat bot, which will be able to:

• answer programming-related questions (using StackOverflow dataset)
• chit-chat and simulate dialogue on all non programming-related questions

For a chit-chat mode will use a pre-trained neural network engine available from ChatterBot.