Machine Learning For Dummies

To attract a world-class team, your company has to offer a problem that’s exciting enough to entice the people needed from other organizations

machine learning algorithms currently can’t feel, think independently, or create anything

A single learner algorithm can learn many different things, but not every algorithm is suited for certain tasks

training is the process whereby the learner algorithm maps a flexible function to the data. The output is typically the probability of a certain class or a numeric value.

training is the process whereby the learner algorithm maps a flexible function to the data. The output is typically the probability of a certain class or a numeric value

Everything in machine learning revolves around algorithms. An algorithm is a procedure or formula used to solve a problem.

This book follows the Bayesian tribe strategy, for the most part, in that you solve most problems using some form of statistical analysis

The ultimate goal of machine learning is to combine the technologies and strategies embraced by the five tribes to create a single algorithm (the master algorithm) that can learn anything

five tribes (schools of thought) that make machine learning feasible

The essence of the matter is that machine learning provides just the learning part of AI, and that part is nowhere near ready to create an AI of the sort you see in films.