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…
Building a machine learning model involves a sequence of tasks from data cleaning to feature engineering. In scenarios where these steps need to be repeated, for instance when data is…
In Python, a generator function allows us to iterate over particular elements such as a list, and returns the following element every time we call it. Now, one might think…
In the development of self driving vehicles, a cornerstone concept that engineers rely on is the "bicycle model." This abstract representation simplifies the complex dynamics of a car into a…
Modern vehicles monitor their dynamics at every fraction of time to maintain vehicle stability. For this, significant amount of data flows from every sensor into the ECUs and appropriate action,…
