If you've ever argued with a Tesla fanboy, you know that the "LiDAR vs. Camera" debate in self-driving tech is hotter than a GPU running stable diffusion. Some say LiDAR…
Imagine you're learning to play the guitar. Instead of figuring everything out from scratch, you watch an experienced musician, follow their techniques, and build upon their skills. That’s exactly how…
Ever felt like your model’s nearly perfect but needs that little extra "boost"? Your model is not too bad to be thrown away in trash but also not good enough…
In the previous guide on Support Vector Machines, we understood the basic implementation and functioning of the machine learning classifier. In this post, I’ll walk you through three practical examples…
YOLO (You Only Look Once) has long been a popular machine learning model for real-time object detection, offering an impressive balance between speed and accuracy. Since its existence, the model…
A machine learning model learns over the data it is trained and should be able to generalize well over it. When a new data sample is introduced, the model should…
In my previous blog on "Build your *FIRST* Machine Learning using Python", I mentioned that a general flow in a machine learning project involves importing the data, splitting it into…
When entering into the world of machine learning, one of the first concepts you encounter is error metrics or cost functions. These metrics help us understand the model performance by…
In the previous blog on Confusion Matrix 101: Understanding Precision and Recall for Machine Learning Beginners, we understood the meaning of precision and recall which are important metrics while building…
When we build a machine learning model, choosing the appropriate metric is the key factor for the feasibility of that model. This factor is only realizable when a model is…
