Introduction to Artificial Neural Networks through R
During this session, we will understand the basic concepts around Artificial Neural Networks using R to import and process 70.000 images of handwritten digits.
Recognizing handwritten characters is a challenge for the FinTech industry when trying to digitalize millions of invoices and contracts in developing countries. During this session, we will understand the basic concepts around Artificial Neural Networks to build a prototype to solve part of this challenge. We will use R, a free programming and software environment for statistical computing, to import and process 70.000 images of handwritten digits. Understanding the capabilities of deep learning will open a new spectrum of possibilities in all industries. Object recognition in images, anomaly detection and surveillance are just a few examples of the common use cases for Neural networks.
Chief Technology Officer at Binfluencer and Professor in Machine Learning at IE Business School
He is an Ex-McKinsey Data Scientist; software engineer specialized in Artificial Intelligence and has a master degree in Business Analytics and Big Data by the IE Business School. He is also an adjunct professor in machine learning at the same university.