As businesses grapple with increasing amounts of data and search for ways to use it effectively, they're turning more and more to machine learning and deep learning. Both models use statistics to make predictions, but there are differences.
Machine learning employs algorithms to identify patterns and make predictions. When the algorithmic model makes a wrong prediction, a programmer must troubleshoot. Deep learning functions similarly, but its artificial neural network enables it to problem-solve more like a human. It can correct itself in the case of a bad prediction.
The two artificial-intelligence applications can help leaders make complex decisions. Business leaders want to understand the value of predictive analysis and models to develop proprietary data sets that give them a competitive advantage.
Shifting your organization's focus to finding new patterns in data and anticipating future trends can help you capture opportunities and prepare for risks.
MASTERING MACHINE LEARNING
Advanced knowledge of mathematics, statistics, data analysis, and programming is fundamental for a machine learning engineer. To help technical professionals better understand the technology, IEEE Educational Activities is offering a five-course program: Machine Learning: Predictive Analysis for Business Decisions:
Machine Learning in the Age of Enterprise Big Data
Examines the fundamental types of machine learning that drive business insights and reviews advanced computational intelligence for business processes.
Machine Learning in a Data-Driven Business Environment
Learn how to manage multifaceted enterprise data. This course can help you comprehend diverse sources that allow businesses to collect, store, organize, and interpret data.
Sound Business Practices for Data Mining and Predictive Analysis
Explore tools to measure business performance. This course explains how predictive and prospective analytics can deliver insights.
Machine Learning Algorithms, Models, and Systems Integration
Get a better understanding of available software. The course includes best practices for machine learning model integration.
Machine Learning Platforms, Technology, and Tools
Study the computational infrastructure that is necessary for enabling machine learning with big data. This course explains the concepts and techniques necessary for deploying scalable machine learning.
IEEE Educational Activities also offers Enhancing Business Operations With Machine Learning, an on-demand virtual event. It was presented by Grant Scott, assistant professor in the electrical engineering and computer science department at the University of Missouri in Columbia.