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Issue - 143

Worthy Read

This free reference guide will take you back to the basics. You’ll find visuals and definitions on key concepts and questions you need to answer about your teams to determine your readiness for continuous delivery. Download and share with your team.

Building recommender systems today requires specialized expertise in analytics, machine learning and software engineering, and learning new skills and tools is difficult and time-consuming. In this post, we will start from scratch, covering some basic fundamental techniques and implementations in Python. In the future posts, we will cover more sophisticated methods such as content-based filtering and collaborative based filtering.
machine learning

What should be a really simple function has turned into a fifty-line gargantuan that’s too hard to read properly because of the sheer number of lines. The culprit; a seriously long if-elsif-else chain. But not to fear; there’s a better way!

TypeError: object() takes no parameters

Modern microprocessors are a very complex piece of machinery with a lot of different parts. I've learned assembler and microprocessors in my undergraduate course some years ago but, as I've been working on higher level software languages for quite some time now, I forgot many things. Lately I decided to revisit some of the topics on microprocessors and to build a very simple model of a microprocessor in Python for education purposes (I work as CS professor). You can find the final source code and some samples at

Plotly has a new member of the Plotly.js chart family: The Sankey diagram. Jupyter notebook is at above the footnote of the blogpost.

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I got my hands on a dataset on traffic accidents in Metro Manila early this year, and decided to enter the realm of data science with a simple cleaning and visualization project. The primary goal: supplement the dataset’s human readable location data with geographic coordinates.
data science

Have you ever noticed that Python supports integers of any size? Here is a quick glance at it.

In the last post, we saw how we could use simple correlational techniques to create a measure of similarity between the books’ users based on their rating records. In this post, we will explain how you can use those same sort of similarity metrics to recommend books to a book’s readers.
machine learning

I wanted to make a short post on using Slack’s incoming webhooks feature to post messages to Slack using the human-friendly Requests API in Python3.

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Code packages available in PyPI contained modified installation scripts.

In this short blogpost, I will explore few topics to illustrate the interactivity of the jupyter environment and the python availability of high quality libraries in the ecosystem.

The term desktop notifications refer to a graphical control element that communicates certain events to the user without forcing them to react to this notification immediately. In other words, it is a simple application which produces a notification message in form of a pop-up message on desktop.
desktop app

Geospatial analysis applies statistical analysis to data that has geographical or geometrical components. In this tutorial, we’ll use Python to learn the basics of acquiring geospatial data, handling it, and visualizing it. More specifically, we’ll do some interactive visualizations of the United States!

The current blog deals with the case how to implement web analytics in Python. I am enthusiastic about the options that are available inside Google Analytics. Google Analytics has a rich variety of metrics and dimensions available. It has a good visualization and an intuitive Graphic User Interface (GUI). However, in certain situations it makes sense to automate webanalytics and add advanced statistics and visualizations. In the current blog, I will show how to do that using Python.

Transit networks with higher frequency and shorter waiting times will yield a more reliable and empowering experience for passengers than those with lower frequency and longer waiting times.

I needed a quick way to remotely perform system operations: adjusting & muting the system volume, screen brightness, and putting the display to sleep. After exploring several options, I found none of them to be viable for me, and thus, I set out to develop my own solution.

In the example below, I’ve demonstrated how this can be done using Python in a way that doesn’t require deep knowledge of CUDA and its intricacies. For this example, I suggest using the Anaconda Python distribution, which makes managing different Python environments a breeze. Follow the download and setup instructions for Anaconda as given here for your specific operating system.


How to share code snippets from command line?

Some time ago we decided to move part of our logic to celery. Several tasks was wrote and in one of them bash script was called, and this task never applied correct: first half of script was executed and then halted. I found that script running in processes, and can’t understand why it just stoped. Then I set some breakpoints in bash script and realised, that script stops at

From dummy variables to Deep category embedding and Cat2vec?—?Part 1 (Basic Methods).
machine learning

You can join two GeoPandas GeoDataFrames through conventional means with merge, but you can also use sjoin to capitalize on the spatial relationship between two frames.

text processing


face-alignment - 165 Stars, 25 Fork
2D and 3D Face alignment library build using pytorch

MetaDockers - 44 Stars, 8 Fork
Responsible for visualization the vulhub or docker.

mygf-instagram - 34 Stars, 1 Fork
Like posts of my girlfriend's Instagram using web api, don't need any api key and access tokens just login and password

graphscii - 3 Stars, 0 Fork
Print ASCII graphs in the terminal.

xlsx2csv_gui - 2 Stars, 0 Fork
Convert excel xlsx file's table to csv file, A GUI application on top of python/pyqt and other opensource softwares.