10 Amazing Articles On Python Programming And Machine Learning Originally Posted Here A lot is happening in the world of Python. Support for Python 2 is ending, more and more companies are referencing Python in job descriptions and it continues to gain new libraries and more support. Since there is so much changing so fast, we got some of our favorite articles. We hope they help you on your Python programming journey. Python 2 EOL: How to survive the end of Python 2 Python 2 support ends in 2020. Here’s what you can do if you’re stuck with Python 2 in what is fast becoming a Python 3 world By Serdar Yegulalp On January 1, 2020, the 2.x branch of the will no longer be supported by its creators, the Python Software Foundation. This date will mark the culmination of a drama that has stretched on for years — the transition from an older, less capable, widely used version of Python to a newer, more powerful version that still trails its predecessor in adoption. Python programming language Read More Here What do companies expect from Python devs in 2019? By Andrew Stetsenko What skills do I need to succeed as a Python dev in 2019? Jointly with our team, we took 300 job specs for Python developers, scrapped from StackOverflow, AngelList, LinkedIn, and some fast-growing tech companies worldwide. From all these descriptions, we extracted the skills which were mentioned the most frequently, and here they are. (The numbers refer to the number of mentions.) Read More Here Asynchronous Programming in Python: A Walkthrough David Bolton When we talk about program execution, “asynchronous” means that the program doesn’t wait for a particular process to complete, but carries on regardless. An example of asynchronous programming is a program writing to a log file: Although it’s possible it might fail (for instance, because the log filled up the disk space), most times it doesn’t, and you can write your program to call the log routines asynchronously (or ‘fire and forget,’ as I call it). Asynchronous execution means the main program runs a little faster. Your logging code should be written so that if it does fill the disk, it just stops logging rather than crashing. Read More Here Buggy Python Code: The 10 Most Common Mistakes That Python Developers Make By Martin Chikilian Python’s simple, easy-to-learn syntax can mislead — especially those who are newer to the language — into missing some of its subtleties and underestimating the power of the . Python developers diverse Python language With that in mind, this article presents a “top 10” list of somewhat subtle, harder-to-catch mistakes that can bite even some more in the rear. advanced Python developers (Note: This article is intended for a more advanced audience than Common Mistakes of Python Programmers , which is geared more toward those who are newer to the language.) Read More Here Creating Heatmap From Scratch in Python Heatmap is frequently used to visualize event occurrence or density. There are some Python libraries or GIS software/tool that can be used to create a heatmap like QGIS, ArcGIS, , etc. Unfortunately, this post won’t discussed how to create a heatmap using those software/tool, but more than that, we will write our own code to create a heatmap in Python 3 from scratch using Python common library. Google Table Fusion The algorithm which will be used to create a heatmap in Python is Kernel Density Estimation (KDE). Please refer to this post ( ) to get more explanation about KDE and another post ( ) which give an example how to calculate intensity for a point from a reference point using KDE. QGIS Heatmap Using KDE Explained Heatmap Calculation Tutorial Read More Here How to build your own Neural Network from scratch in Python By James Loy What’s a Neural Network? Most introductory texts to Neural Networks brings up brain analogies when describing them. Without delving into brain analogies, I find it easier to simply describe Neural Networks as a mathematical function that maps a given input to a desired output. Neural Networks consist of the following components Read More Here What exactly can you do with Python? Here are Python’s 3 main applications. “What exactly can I use Python for?” Well that’s a tricky question to answer, because there are so many applications for Python. But over time, I have observed that there are 3 main popular applications for Python: Web Development Data Science — including machine learning, data analysis, and data visualization Scripting Read More Here Python programming language gets speed boost from latest PyPy interpreter By Nick Heath Good news for Python developers, thanks to a new release of the already speedy PyPy interpreter that promises to be the fastest version yet. If you’re programming using Python then an important choice is whether to run your code using the main CPython interpreter or an alternative such as PyPy, with each option having pros and cons. PyPy’s USP is its speed, with its integrated Just In Time (JIT) compiler allowing it to run some Python code some 7.6 times faster than CPython . according to benchmarks Read More Here How to collect, customize, and centralize Python logs By Emily Chang and Nils Bunge Python’s logging module basics The logging module is included in , which means that you can start using it without installing anything. The logging module’s method is the quickest way to configure the desired behavior of your logger. However, the recommends creating a logger for each module in your application — and it can be difficult to configure a logger-per-module setup using basicConfig() alone. Therefore, most applications (including web frameworks like ) automatically use file-based or dictionary-based logging configuration instead. If you’d like to get started with one of those methods, we recommend . Python’s standard library basicConfig() Python documentation Django skipping directly to that section Three of the main parameters of basicConfig() are: Read More Here Are You Interested In Learning About Data Science Or Tech? Learning Data Science: Our Favorite Data Science Books What Is Data Science Really As Told By An Ex-FAANG Data Scientist Learning Data Science: Our Top 25 Data Science Courses How Algorithms Can Become Unethical and Biased How To Load Multiple Files With SQL How To Develop Robust Algorithms Dynamically Bulk Inserting CSV Data Into A SQL Server 4 Must Have Skills For Data Scientists SQL Best Practices — Designing An ETL Video

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