AdaBoost (Adaptive Boosting) is a popular boosting algorithm that combines multiple weak classifiers to create a strong classifier. The algorithm works by iteratively adjusting the weights of the training instances and focusing more on the misclassified instances in each iteration using a weighted sampled distribution. [Read More]

Correlations are like two peas in a pod - they just can’t be separated. In machine learning, correlations are like the secret ingredient that makes our models stand out. They help us identify patterns and relationships between features, and guide us in selecting the most relevant variables to predict our... [Read More]

Logistic regression is a powerful and versatile statistical technique that has been widely used in various fields, including machine learning, statistics, and social sciences. It is a simple yet effective method for modeling the relationship between a binary response variable and one or more predictor variables. [Read More]

Having a passion for mathematics, I was delighted to find out that Machine Learning models are using algebra under their hoods. As a result, I decided to create this mini-blog series called “Machine Learning” demolished! The purpose of the blogs is for me to refresh my memory on the optimisation... [Read More]

Going back to my early days in data science, I was so excited to get my hands on raw data, curate it and feed it to my machine learning model! I felt like I was hacking the world - especially when I was getting unrealistically high “accuracy” metrics! [Read More]