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…
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…
Google has introduced its ‘largest’ and ‘most capable’ large language model (LLM), which goes by the name of Gemini, to the world. Google's Gemini 1.0 AI model is the “start of a new era”…
You might have just learned some theory on machine learning and looking for a small, hands-on project to get hold of it. In this blog, we are going to build…
Splitting the available data into training and test sets help us evaluate the performance of the model. The model is trained using the training set and its generalization capability is…
A few months ago, I was working on a project where I had to train and develop a regression model that predicted the price of a vehicle given its features…
