Which ML algorithm to use if we have categorical data, numeric data, derived data (derived from) other variable in our data set? I am a beginner in Data Science. I have a data set which contains numerical data, categorical data and derived data (derived from other columns). The target column (dependent) is binary. Which Machine Learning algorithm will predict my target column most accurate?
This question is way too vague, you just describes pretty much a standard situation. Which algorithm / method you use depends entirely on your objective and data. You should provide more information if you want a specific answer. Since your dependent variable is binary you are interested in classification, popular algorithms are Random Forests, Logistic Regression, K-means, etc.