Python Weekly (Issue 366 September 27 2018)

Python Weekly - Issue 366Â

September 27, 2018

Python Weekly

Welcome to issue 366 of Python Weekly. Are you looking for a job? If yes, then make sure to check an amazing platform from our sponsor this week, Vettery.

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Articles, Tutorials and Talks

A tutorial on how to build a custom Google Assistant skill using custom and open source NLP and dialogue management system which enables the Google Assistant to handle more complex conversations. 

Error metrics are short and useful summaries of the quality of our data. We dive into four common regression metrics and discuss their use cases.

Learn how you can create a Python GUI in 2018.

In this video I build a web server in Python from scratch to remotely control the on-board RGB LED of a WiPy 3.0 development board. The end result is like a custom smart light.

I this article I’ll describe the steps I went through in the process of grasping why del() is valid Python and exactly what it does, sharing a few techniques that can prove to be useful to others in understanding funny looking Python code tidbits, like this one felt to me.

From TLS to authentication, “crypto” is used for a lot more than just currencies. This post will dive into modern cryptography, an overview of how symmetric and asymmetric cryptography works, and its everyday use cases.

It is estimated that by 2020, chatbots will be handling 85 percent of customer-service interactions; they are already handling about 30 percent of transactions now. In this post, we will build a simple retrieval based chatbot based on NLTK library in python.

This guide walks you through a exercise in consuming, transforming and analysing a data dump of the English language version of Wikipedia.

Without a planned structure, larger Python projects can become a complicated web of interdependencies. The Rocky River is an architectural pattern to help make larger projects easier to work with.

Python Jobs of the Week

We are creating a compelling new retail model centered around providing fast and personal service. We are using a light web framework (Python, Pylons, SQLAlchemy, Backbone.js) combined with modern but proven components (Redis, Elasticsearch) all running on Amazon Web Services (EC2, RDS, S3, CloudFront).

Interesting Projects, Tools and Libraries

Create Siri Shortcuts with Python.

Pypeline is a simple yet powerful python library for creating concurrent data pipelines.

Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!

Financial portfolio optimisation in python, including classical efficient frontier and experimental methods.

Efficient environment variables management and typing for python.

Build and run Containers.

For When You Want To Clean All That Garbage.

apricot implements submodular selection for the purpose of selecting subsets of massive data sets to train machine learning models quickly.

An API Client package to access the APIs for NBA.com

Let's make a SQL parser so we can provide a familiar interface to non-sql datastores!

Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.

A simple, flexible, and extensible template for PyTorch.

New Releases

This is the first version of Matplotlib to only support Python 3. Highlights of this release include:

  • GUI backend is selected at run-time based on what toolkits are installed. A GUI toolkit will not be selected on a headless server.

  • New cyclic color map *twilight*

  • Improvements to automatic layout of titles, ticks, and GridSpec

  • Many bug fixes!

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