Python3 implementation of the Schwartz-Hearst algorithm for extracting abbreviation-definition pairs.

A framework for elegantly configuring complex applications.

Streamlit is the first app framework specifically for Machine Learning and Data Science teams.

So you can stop spending time on frontend development and get back to what you do best.

Introducing Streamlit, an app framework built for ML engineers.

150+ Python Interview Questions and Answers to make you prepare for your upcoming Python Interviews. This collection of top interview questions will boost your confidence and increase the chances to crack interview in one go.150+ Python Interview Q

These resources will get you started and well on your way to proficiency with Python.

Super fast list of dicts to pre-formatted tables converter library for Python 2/3.

Websauna is a full stack Python web framework for building web services and back offices with admin interface and sign up process.

Arcade is an easy-to-learn Python library for creating 2D video games.

It is ideal for people learning to program, or developers that want to code a 2D game without learning a complex framework.

For research purposes, and to analyze the content of a Telegram channel, you may need the channel’s data in a clean JSON format.

Here there is a Python script to get data from Telegram channels. It has two main files: One for getting a member’s data from a channel, and second, to get the channel’s messages.

The script saves this data into JSON files; you can use them for analysis or to import into your databases.

Visual scripting framework for python.

Frustrated by programming language shortcomings, Guido van Rossum created Python. With the language now used by millions, Nick Heath talks to van Rossum about Python's past and explores what's next.

This article compares the performance of several approaches when summing two sequences element-wise with different Python loops.

Is there a way to conveniently define a C-like structure in Python? I'm tired of writing stuff like:

class MyStruct():
    def __init__(self, field1, field2, field3):
        self.field1 = field1
        self.field2 = field2
        self.field3 = field3

In a nutshell, it is a type of statistical model used for tagging abstract “topics” that occur in a collection of documents that best represents the information in them.

Many techniques are used to obtain topic models. This post aims to demonstrate the implementation of LDA: a widely used topic modeling technique.

pyLDAvis is a python library for interactive topic model visualization. It is a port of the fabulous R package by Carson Sievert and Kenny Shirley. They did the hard work of crafting an effective visualization. pyLDAvis makes it easy to use the visualiziation from Python and, in particular, Jupyter notebooks.

To learn more about the method behind the visualization, it is possible to read the original paper explaining it.

This notebook provides a quick overview of how to use pyLDAvis.

This article introduces how to build a Python and Flask based web application for performing text analytics on internet resources such as blog pages. To perform text analytics I will utilizing Requests for fetching web pages, BeautifulSoup for parsing html and extracting the viewable text and, apply the TextBlob package to calculate a few sentiment scores.

A simple walkthrough of what RNNs are, how they work, and how to build one from scratch in Python.

A curated list of applied machine learning and data science notebooks and libraries across different industries.