Machine Intelligence : Demystifying Machine Learning, Neural Networks and Deep Learning

Non-Parametric Models:

Based on the above description, we can classify machine learning use cases into 2 categories: – Decision support use cases – Cognitive use cases

2.2 Project Methodology

Number of data records available can also influence the choice of the machine learning algorithm. Machine learning algorithms like support vector machines (SVM) can work with fewer training records whereas neural networks and deep learning algorithms require large amounts of data to be able to train the model effectively.

Classification:

Machine learning models like decision trees and support vector machines (SVM) are inherently non-probabilistic in their predictions.

1.1 Introduction

Machine Learning: Machine learning is a set of tools and techniques, in which intelligence is learned by algorithms and not induced. These systems analyze historical data patterns to extract intelligence and convert them into business rules.

Classification Based on Nature of the Algorithm: Machine learning algorithms are broadly classified into 3 categories based on the nature of the algorithm.