We know that you’ve probably heard of object oriented programming (OOP), but outside of designing games, when is best to use it for data science? We haven’t used OOP much until recently when we refactored a data science project code base. In this article, we give a brief refresher for OOP and discuss our top […]
Staying Up-To-Date on AI/ML
Great Email Newsletters on AI/ML All newsletters are released weekly. Import AI – AI newsletter that summarizes recent news articles and research; I enjoy how honest and succinct this newsletter is; also like that the implications of new algorithms are always discussed by Jack, who is an advocate for improved ML model explicability and data […]
R vs Python
I generally reach for Python when building data science pipelines, however I discovered R before I decided to invest in learning Python. R has saved me lots of time when it came to quickly and easily preparing nice-looking plots for research. It begs the question of where is R better than Python for certain purposes? […]
Export Images to PowerPoint in Python
Data Scientists spend a significant amount of time visualizing data for storytelling or conveying insights to end users of a data product. Often, the ability to succinctly and accurately explain the methods used and insights derived hinges on the medium of communication and time taken to prepare visualizations. In order to limit time spent on […]
Exporting Richly Formatted Text In Python
Today, I wondered whether I could automatically save an image of colored text from the Python console. I was looking for a way to display very long strings that automatically wrapped to its container, so I avoided the dreaded run-on string that never ends. Also, could I save the image elegantly with high resolution? In […]
Fun Hacks for your Python Console
Hack #1: Color Text in Your Terminal You can change the colors of text shown in your Python terminal console using ANSI escape character sequences! Or you can use the colorama library to make the process a bit easier and more streamlined. Colorama works across all the platforms i.e. Windows, Mac OS and Unix. First, […]
Building Recommendations Systems
Recommendations systems are good for matching users to their favorite products and are incredibly popular. In fact you have likely used a recommendation system at least once in your life. For example, Amazon uses recommendation systems to suggest new exciting products to purchase based on users’ previous purchase patterns and those similar users. Netflix also […]
Recurrent Neural Networks in PyTorch
Feed forward networks cannot learn from the past, but Recurrent Neural Networks (RNNs) can learn by accepting data in a sequence. Examples of applications for RNNs include the text autocomplete feature on your phone and performing language translations. Recurrent Neurons (RNs) act as the building blocks of RNNs. The difference between RNs and feed forward […]
Fastai’s Practical Deep Learning for Coders Course Release – 2020 Update!
On Aug 21st, 2020, fastai released a new version of their Practical Deep Learning for Coders -Part 1 course. This course is a must-take for new and intermediate deep learning practitioners. It is well done and teaches you intuition without drowning you in theory. The only prerequisites are some high-school math, and a year of […]
How Genetic Algorithms Work
Genetic algorithms (GAs) are inspired by biology where only the fittest genes survive. It is based on Charles Darwin’s Natural Selection theory. We start with 2 parent chromosomes that each contain an ordered set of genes. Each parent contributes some of their genes when they mate to create children chromosomes. There is a randomness to […]