Branch of Machine Learning dealing with Unsupervised Learning.
In this blog post, we’ll dive deep into the fascinating world of machine learning frameworks – We’ll explore two famous and influential players in this arena: TensorFlow Lite and PyTorch Lightning. While they may seem like similar tools at first…
This post will help break the myths surrounding a unique but common machine-learning algorithm called SVG. One of the most debated (silly) topics is whether SVG is a machine-learning algorithm or not. Believe it or not, SVG is a machine-learning…
I’ll be honest; choosing the right algorithm for machine learning can be one of the most challenging parts of our jobs. Don’t worry; we’re here to help. In this article, we’ll be breaking down the process of selecting the perfect…
Every computer science student had to deal with sorting algorithms while learning how to code. While traditional sorting algorithms have been in use for decades, the rise of machine learning has given birth to a new type of sorting algorithm…
We’ve all been there, cleaned up our dataset, and realized it’s incredibly noisy. Should you get rid of the noise? Why is it even there? And what even is noise? In this blog post, we’ll look at what noise is,…
Epochs in machine learning can be confusing for newcomers. This guide will break down epochs and explain what they are, how they work, and why they’re important. We’ll also dive deep into Epochs’ relationship with Batch size and iterations. Deep…
Data is the heart and soul of machine learning. Without data, data scientists cannot create impactful machine-learning algorithms (duh). While this seems pretty standard, the type of data makes a huge difference when trying to perform data analysis. And sometimes, when we…
Machine learning is a vast and complex field that covers many different concepts. While there is some jargon to get up and running in machine learning, some of the ideas behind this jargon are very simple. This guide will focus…
Machine learning is a vast and complex field that has inherited many terms from other places all over the mathematical domain. It can sometimes be challenging to get your head around all the different terminologies, never mind trying to understand…
One common task you will encounter while working in machine learning is clunky datasets that need cleaning. This involves dealing with inconsistencies and errors in the data and data that wouldn’t “make sense” for our models in their current form.…