A machine learning algorithm is the process that does the learning and creates a model to address a ML problem

So, ML model is the result the learning process of a ML alogrithm, is the “program” that is saved after training, later loaded and used to make predictions on new data. e.g a) The coefficients from a linear regression, b) The weights and structure of an artificial neural network, c) The decision trees from a random forest.

ML algorithms can be grouped either by its learning style or by its function/form in the way it creates the model

Must learn algorithms for 2018

• Decision tree
• Random forest
• Linear Regression
• Logistic regression
• Support vector machine
• Naive Bayes
• k-NearestNeighbor
• k-means
• Adaboost
• Neural network
• Markov