This is the multi-page printable view of this section. Click here to print.

Return to the regular view of this page.

Mathmatics

Applied Mathematics the foundational discipline that guides everyone to ensure the findings are indeed backed by reality. As scientists we’re primarily interested in probability interpretations.

subpages:

  • Subjective-Intuition
  • Probability
  • Predictive Modelling

1 - Predictive Modeling

Predictive modeling is an area of study to help humans leverage advanced mathematical approaches to find patterns in historical data upon which future predictions can occur.
Knowledge Graph Connections
Lifecycle of Data Science Lifecycle Requires Feature Engineering Informs design of Knowledge Management Follows Scientific Method Formalizes STEAM Knowledge Graph

1.1 - Data Science Lifecycle

The data science lifecycle enables teams to ‘Dare to Dream’ about how all the disciplines can resonate and shape the solution — from problem framing through model deployment and monitoring.
Knowledge Graph Connections
Lifecycle of Predictive Modeling Step in Feature Engineering Parallel to Scientific Method Requires Big Data

1.2 - Feature Engineering

enables teams to ‘Dare to Dream’ about how all the disciplines can resonate and shape the solution

1.3 - Non Linear Regression Models

enables teams to ‘Dare to Dream’ about how all the disciplines can resonate and shape the solution

1.4 - Pre-processing Data Set

enables teams to ‘Dare to Dream’ about how all the disciplines can resonate and shape the solution