How to create an image data augmentation pipeline to generate tons of synthetic data points

Data augmentation is a technique to solve model overfitting without collecting and labeling new data points. Lot’s of machine learning practitioners use this technique in most of their models. Although any image processing library can do image data augmentation, a dedicated package do it with less effort and better results. Albumentation is one such tool we can use. It could even handle annotated image augmentation faster and cleaner.
Image by Pixabay from Pexels.

After months of hard work, you and your team have gathered a vast amount of data for your machine learning project.

The project budget is almost over and what’s left is only enough for training the model.

But as soon as you train the model, you start to see the…

A simple trick to make your charts interactive and visually appealing

Photo by Sharon McCutcheon from Pexels

Great visualization leads to excellent insights.

Almost every data scientist who uses Python also uses Pandas. It’s the de-facto Python library for data wrangling. Pandas out of the box offer some great visualization for common chart types.

But the defaults aren’t the best.

We could make it even better with…

A handy Python package to save a ton of coding time and improve readability with shell-styled pipe operations

Pipe is a Python library that helps in chaining multiple data manipulation operations in to a single statement. It takes a shell type operation piping approach. There are many operations come along with the library such as dedup, sort, where, groupby, ect. If they aren’t enough, you can create your own pipe operations from functions.
Use pipe operations to create a chain of multiple data manipulations in a single statement. Photo by Joey Kyber from Pexels

Python is already an elegant language to program. But it doesn’t mean there is no room for improvement.

Pipe is a beautiful package that takes Python’s ability to handle data to the next level. It takes a SQL-like declarative approach to manipulate elements in a collection. …

The bad, the lovely, and the smart ways of debugging your Python code.

Python has a variety of ways for debugging. Most beginners don’t understand the different options available to them. Here we discuss several techniques to help use the best way to find out issues and fix them in their code.
Tools and techniques for debugging Python scripts — Photo by Anete Lusina from Pexels

It took me some time to grasp the idea of debugging.

I’m sure that’s common with most code newbies. To me, as a self-taught Python programmer, locating issues and fixing them in the quickest possible way was challenging.

But over the years, I learned several techniques to spot bugs in…

You can build installable web apps with Python web frameworks. Here’s a guide to creating one with Django.

You can build installable web apps with Python web frameworks. Here’s a guide to creating one with Django.
Photo by Miguel Á. Padriñán from Pexels

Python is a fantastic programming language that you can use to create amazing things on the web.

Python frameworks such as Django and Flask power a large portion of the internet, and Python has emerged as one of the most popular backend programming languages for many reasons.

Python is also…

Machine learning has siblings.

Machine Learning Vs. Artificial intelligence: What’s the difference? Machine learning is one of the subfields of Artificial Intelligence. It refers to the process of getting a computer to learn from data without being explicitly programmed.
Machine Learning Vs. Artificial intelligence: What’s the difference? — Photo by Pavel Danilyuk from Pexels

Artificial Intelligence is not a thing.

It’s more of an umbrella term that brings together several subfields of computer science. This field is divided into multiple parts, algorithms, theories, and applications.

Each has different goals and methods to pursue them. …

Thuwarakesh Murallie

Data scientist @ Stax, Inc & Top writer in Artificial Intelligence.

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