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- Python Weekly (Issue 363 - September 6 2018)
Python Weekly (Issue 363 - September 6 2018)
Python Weekly - Issue 363
Python Weekly
Welcome to issue 363 of Python Weekly. Let's get straight to the links this week.
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News
Articles, Tutorials and Talks
In this series, we will be learning how to build a full-featured Django application for scratch. We will learn how to get started with Django, use templates, create a database, upload pictures, create an authentication system, and much much more.
In this tutorial you'll dig deeper into Python's lexical structure and start arranging code into more complex groupings. You'll learn about the syntactic elements that comprise statements, the basic units that make up a Python program.
An Intuitive Explanation of Convolutional Neural Networks.
A guide for using and understanding the random forest by building up from a single decision tree.
In this tutorial, you will learn how to perform semantic segmentation using OpenCV, deep learning, and the ENet architecture. After reading this guide, you will be able to apply semantic segmentation to images and video using OpenCV.
It’s time for another deep-dive into Python brokenness and the pain that is POSIX system programming, this time with exciting and not very convincing shark-themed metaphors! Most of what you’ll learn isn’t really Python-specific, so stick around regardless and enjoy the sharks.
In this step-by-step tutorial you'll learn how to work with conditional statements in Python. Master if-statements and see how to write complex decision making code in your programs.
One of the fun parts in using serverless is the fact that you can try out new ideas and provision them in a flick of a finger. I’ve mentioned more than once that s3 is a powerful tool that can be used as more than an elastic persistent layer. In this post, I’m going to demonstrate how to use s3 as a scheduling mechanism to execute various tasks.
Using PyQt to build a GUI for your webcam.
Interesting Projects, Tools and Libraries
Bowler is a refactoring tool for manipulating Python at the syntax tree level. It enables safe, large scale code modifications while guaranteeing that the resulting code compiles and runs. It provides both a simple command line interface and a fluent API in Python for generating complex code modifications in code.
Playground and cheatsheet for learning Python.
lazydata is a minimalist library for including data dependencies into Python projects.
Headless chatbot that detects spam and posts it to chatrooms. Uses ChatExchange, takes questions from the Stack Exchange realtime tab, and accesses answers via the Stack Exchange API.
Music Theory for Humans.
PyTorch implementations of algorithms for density estimation
Download SoundCloud music at 128kbps with album art and tags.
A high-level, rapid development framework for machine learning projects.
Starlette is a lightweight ASGI framework/toolkit. It is ideal for building high performance asyncio services, and supports both HTTP and WebSockets.
Easy async ORM for python, build with relations in mind.
Render reproducible examples of Python code for posting to GitHub/Stack Overflow.
Yoke is a hackable Android gamepad for Linux.
New Releases
Upcoming Events and Webinars
Tutorial: Scaling Flask with Kubernetes. In this talk, Michael Herman will first explain Kubernetes and container orchestration from a high-level and then he'll show how to deploy a Flask-based microservice (along with PostgreSQL and Vue.js) to a manged Kubernetes cluster.
There will be following talks
Keeping code beautiful: Python tools for maintaining high quality code.
I Found a Python Interpreter Bug
Using ARIMA Model to Forecast Time Series in Python
Geopandas
There will be following talks
Introduction to Webscraping and Its Future in Big Data
Learning how Computing and Human Interaction Interlink
What the Zen of Python can teach us about Data Ethics
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