Machine Learning
Machine Learning is subset of AI ( Artificial intelligence) Machine Learning Workflow: Understanding problem and objective Reading from data sources EDA - Exploratory Data Analysis Data Cleaning Modeling Deployment and Reporting Use Algorithms which figures out rules for us instead of you (developer) writing rules for each input. INPUT -> Classifier ->OUTPUT Classifier - we train classifier. Classifier is function which take data as input and assigns labels to it as an output. e.g. decision is a type of classifier "if classifier is box of rules than learning algorithm is procedure that creates them" since it finds patterns in training data in scikit training algorithm is included as fit() function. Supervised Learning: collect & Train data -> Train Classifier -> Make prediction Training Data: feature 1, feature 2, .... feature n -> Label e.g. weight, Texture -> Label 150g, Smooth -> Apple 130g, Bumpy-> O