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…
When we talk about classification problems, the basic machine learning model that we would generally prefer is logistic regression. It is simple to implement and performs well on large datasets.…
There are days when we just do not want to do anything except lie down in bed all day. There are also days when we are completely on fire and…
A major project can consist of thousands of lines of code with several other libraries that are used as dependencies. The code, however, does not magically know the existence of…
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 post on gradient descent, I explained briefly what gradient descent means and what mathematical idea it holds. A basic gradient descent algorithm involves calculating derivatives of the…
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…
It is not until you work on an important project that you realize the importance of small things in programming. For me, it is the header file in C++. "Why…
