Python Weekly (Issue 341 - April 5 2018)

Python Weekly - Issue 341Â

Python Weekly

Welcome to issue 341 of Python Weekly. We have a mobile friendly template now, which was long overdue. Hope you like it.

From Our Sponsor 

Track down issues quickly with Datadog's distributed request tracing for Python applications. Get end-to-end visibility into your application to find slow queries, bugs, and inefficient code.

News

A Library for Reusable Machine Learning Modules in TensorFlow.

Articles, Tutorials and Talks

We explore building generative neural network models of popular reinforcement learning environments. Our world model can be trained quickly in an unsupervised manner to learn a compressed spatial and temporal representation of the environment. By using features extracted from the world model as inputs to an agent, we can train a very compact and simple policy that can solve the required task. We can even train our agent entirely inside of its own hallucinated dream generated by its world model, and transfer this policy back into the actual environment.

Use this tutorial to learn how to create your first Jupyter Notebook, important terminology, and how easily notebooks can be shared and published online.

What is Git,  what is GitHub, and what's the difference? Learn the basics of Git and GitHub from the perspective of a Pythonista in this tutorial.

In this article I’m going to explain what keyword arguments are and why they’re used. I’ll then go over some more advanced uses of them that even long-time Python programmers may have overlooked because quite a few things have changed in recent versions of Python 3. If you’re already an experienced Python programmer, you might want to skip to the end.

Convolutions are an important tool in modern deep neural networks (DNNs). This post is going to discuss some common types of convolutions, specifically regular and depthwise separable convolutions. The focus will be on the implementation of these operation, showing from-scratch Numpy-based code to compute them and diagrams that explain how things work

How to deploy a Django + Postgres app on Google Cloud’s Flexible App Engine using Gunicorn. Includes configuring a database instance and serving static files from a Google Cloud Storage bucket. Step-by-step guide for complete beginners.

Keep this regex cheat sheet nearby as you code, as a quick, handy reference.

An introduction to the Pytorch deep learning framework with emphasis on how it performs automatic differentiation with the autograd package.

Interesting Projects, Tools and Libraries

A library for transfer learning by reusing parts of TensorFlow models.

A Tool for Moving Things in Python.

Transfer files over WiFi from your computer to your smartphone from the terminal.

Python and C++ code for reading and writing genomics data.

A hobby C compiler created in Python.

A python library for visualizing Artificial Neural Networks (ANN).

Automatically 'summarizes' a video by creating multiple WEBMs or GIFs from a single video. It breaks a video into pieces and generates a WEBM/GIF from each piece. It can do this for each video in your folder with a single click. This is similar to a video thumbnails sheet but in WEBM/GIF form.

A tool to scrape LinkedIn without API restrictions for data reconnaissance.

A powerful Python-based software-defined radio (SDR)

One dependency to rule them all.

Convert text documents to high fidelity audio(books).

New Releases

Upcoming Events and Webinars

There will be following talks

  • Mastering APIs, A Crash Course

  • Python 2 to 3: How to Upgrade and What Features to Start Using

There will be following talks

  • Data Visualization with Plotly for Python

  • S.T.E.A.M. Power: How The Arts Supercharge Technology

  • The Practice of GIS in Indiana

There will be following talks

  • Unwrap the wrapped, decorate the decorated: crash course on decorators

  • Pathfinding in Python

  • HTML5 Live Streaming With GStreamer

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