Python Weekly (Issue 352 - June 21 2018)

Python Weekly - Issue 352Â

June 21, 2018

Python Weekly

Welcome to issue 352 of Python Weekly. Let's get straight to the links this week.

From Our Sponsor 

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Articles, Tutorials and Talks

Learn how to perform face recognition using OpenCV, Python, and dlib by applying deep learning for highly accurate facial recognition.

In this post, we will discuss the history, evolution, and future of our modeling/testing/serving framework, internally referred to as Deepbird, applying ML to Twitter data, and the challenges of serving ML in production settings. Indeed, Twitter handles large amounts of data and custom data formats. Twitter has a specific infrastructure stack, latency constraints, and a large request volume.

This post will outline how to build a classification model to predict which patients are at risk for 30-day unplanned readmission utilizing free-text hospital discharge summaries

In this article, we’re going to build a simple sentiment analysis platform using Flask. Our platform will be able to classify a movie review as either positive or negative. We’ll use the IMDB dataset to build a simple sentiment analysis model, save it, and host it on Heroku. We’ll use Gunicorn to serve our model.

You will see how calculations can be performed on objects in Python. By the end of this tutorial, you will be able to create complex expressions by combining Python objects and operators.

Create great forms across your site. Learn how to customize Django's form rendering, and apply form styles and implementations site-wide to make universal changes to forms across an entire website.

How django-carrot uses PyPRI to store and distribute development build.

Proven and tested hands-on strategies to tackle NLP tasks.

Books

Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction. Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world.

Interesting Projects, Tools and Libraries

Masonite is the rapid application Python development framework that strives for: beautiful and elegant syntax, actual batteries included with a lot of out of the box functionality, and extremely extendable. Masonite works hard to be fast and easy from install to deployment so developers can go from concept to creation in as quick and efficiently as possible. 

Takes in a GIF, short video, or a query to the Tenor GIF API and converts it to animated ASCII art. Animation and color support are performed using ANSI escape sequences.

A runtime mobile application analysis toolkit with a Web GUI, powered by Frida, written in Python.

An easy command line interface for the 2018 World Cup.

CMS (Content Management Systems) Detection and Exploitation suite.

An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors.

Telegram bot for self-testing of anxiety and depression.

A Python application that sends you a SMS when the football team you support scores.

Fast, asynchronous and sexy Python web framework. 

A Python Toolkit for Outlier Detection (Anomaly Detection).

Write music in Vim: Text-based music tracker and midi shell.

An asynchronized Python library to automate solving ReCAPTCHA v2 by audio.

The NES Music Database: use machine learning to compose music for the Nintendo Entertainment System!

Audio MODEM Communication Library in Python.

SNIPER is an efficient multi-scale object detection algorithm.

New Releases

Django 2.1 beta 1 is now available. It represents the second stage in the 2.1 release cycle and is an opportunity for you to try out the changes coming in Django 2.1.

JupyterHub is the multi-user server for Jupyter notebooks, allowing students or researchers to have their own workspace. This release has lots of improvements, especially for stability and performance with large numbers of users.

Upcoming Events and Webinars

The annual SciPy Conference brings together over 700 participants from industry, academia, and government to showcase their latest projects, learn from skilled users and developers, and collaborate on code development. 

Join Trey for a live chat with Paul Gannsle, a maintainer of python-dateutil, who is very knowledgeable about working with dates and times in Python. Paul and Trey will be answering your questions about dates and times, dateutil, timezones, and related topics. This will be a Q&A-driven chat some come prepared with a question or two.

There will be following talks

  • When *Not* To Use the ORM

  • Accountability Counsel using Django to build mini websites to support impoverished communities

There will be following talks

  • Recursion, Fractals, and the Python Turtle Module

  • Zappa serverless with Flask

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