Python Weekly (Issue 465 September 10 2020)

Python Weekly - Issue 465

September 10, 2020

Python Weekly

Welcome to issue 465 of Python Weekly. Let's get straight to the links this week.

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News

The attack hides in Windows systems by impersonating several legitimate programs.

Articles, Tutorials and Talks

Building a social network isn't just a really cool project, but it's also a project that can teach you a lot of new cool things. In this video we will begin by installing the software we need, creating a new Django project and build a simple Twitter clone piece by piece. At the end of this video, you will have a working social network that we will deploy to a live server. 

The first part of a series where we'll dive into the internals of CPython. By doing so we'll understand the language itself at a deeper level. That is the primary goal of this series. 

Have you heard people say that async Python code is faster than "normal" (or sync) Python code? How can that be? In this article I'm going to try to explain what async is and how it differs from normal Python code.

Get an introduction to Python, and be inspired to learn, discover, and create using Python-based data science and machine learning to help generate knowledge about the world beyond Earth.

In this tutorial, you will discover how to use TPOT for AutoML with Scikit-Learn machine learning algorithms in Python.

You run your tests with manage.py test. You know what happens inside your tests, since you write them. But how does the test runner work to execute them, and put the dots, E’s, and F’s on your screen?

`pathlib` is a part of the standard library that helps you deal with file paths. In this video, we explore the library with examples. We also talk about the different `Path` classes that are available to us, and we talk about the relationships between the different classes in the library. And lastly, we talk about some of the caveats of using the library.

Learn about unsupervised algorithms for automatically extracting representative keyword and phrases from documents.

This is an end-to-end tutorial on how to convert a TensorFlow model to TensorFlow Lite (TFLite) and deploy it to an Android app for cartoonizing an image captured by the camera.

This video introduces FastAPI, a framework for creating APIs in a much different style that you're used to in Python.

The article paints a picture for developing a Python API from start to end and provides help in more difficult areas.

A unique python library that extends the python programming language and provides utilities that enhance productivity.

Automated Machine Learning (AutoML) refers to techniques for automatically discovering well-performing models for predictive modeling tasks with very little user involvement. In this tutorial, you will discover how to use Auto-Sklearn for AutoML with Scikit-Learn machine learning algorithms in Python.

In this article, we will be taking an in-depth look at what Django brings to the table by understanding what the generated files and folder do, this will give us a better understanding of the Django framework.

Learn how to develop a next word prediction and autocomplete system akin to that of Google’s Smart Compose. 

Interesting Projects, Tools and Libraries

Find big moving stocks before they move using machine learning and anomaly detection.

Utility function to parallelise pipelines of Python asyncio iterators/generators.

Python library for streaming financial market data.

A library to train large neural networks across the internet. Imagine training one huge transformer on thousands of computers from universities, companies, and volunteers.

Run your own PaaS using Docker, Traefik, and great analytics

A modern audio book player for Linux using GTK+ 3.

Library for scraping websites or APIs at any scale.

Tafferugli is a Twitter Analysis Framework in the form of a web application that is able to filter, collect and analyze tweets.

clifford is a numerical Geometric Algebra (a.k.a. Clifford algebra) package for python.

Upcoming Events and Webinars

There will be following talks

  • How to Establish a Healthy Data Culture

  • AI Fairness 

There will be following talks

  • Evaluation Metrics for Binary Classification: The Ultimate Guide

  •  AI for The Planet. Case study: Deep learning for early wildfires detection of Amazon Rainforest

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