Static.ML

This is the first algorithm in this series of machine learning👾 blogs!!! This series involves various concepts of ML, AI, Reinforcement Learning as well as coding💻 stuff!!! please show some love❤️(It's always a motivation, you know!!🤪). The first algorithm that we'll breakdown🔩 is naive Bayes classifier whereas this blog only involves basic theory (next coming blogs will involve the code and mechanics⚙️ behind). A classifier is a machine learning model that is used to discriminate different objects based on certain features. A Naive Bayes classifier is a probabilistic machine learning model that’s used for the classification task. The crux of the classifier is based on the Bayes theorem.  Example: Let us take an example to get some better intuition. Consider the problem of playing golf🏌. The dataset is represented as below⏬. We classify whether the day is suitable for playing golf, given the features of the day. The co