Detecting the human face is a difficult problem that is faced by experts in the computer vision field. The main reason is because the human face is a dynamic object in which there is a high degree of variability as every face is different.
In his presentation named „Machine learning in the Python world”, Boško will talk about his experience working in the field of machine learning and will mainly discuss Facial expression recognition, eye tracking and other machine learning applications. He will also go over the fundamental steps in programming machine learning in Python and the different field of machine learning.
BFSI is one of the industries where AI/ML is causing significant upheavals in 2021 and beyond. Despite the pandemic, interest in AI and ML implementation has been resilient. According to a survey conducted by the Bank of England, around 40% of respondents said that the relevance of machine learning for future operations has increased, with 10% of institutions on a significant rise. The relevance of machine learning has not decreased at any of the banks. The financial sector is heavily utilizing artificial intelligence and machine learning to automate and simplify processes.
Machine Learning algorithms are based on large amounts of data that need to be processed for the algorithm to learn. GDPR requires companies to comply with regulations that will secure consumer data. But questions have been raised about how this regulation will address automation in analytics as the AI and machine learning market grows. GDPR outlines six data protection principles, and according to Norwegian Data Protection Authority, AI is facing four of them.
There are many reasons why companies integrate Machine Learning into their fundamental activities. But before you decide to transform your business with Machine Learning, you should take a couple of things into consideration to check whether your company is ready for new technology adoption.
While in first part about Frank’s case we explained what the problem was, modus operandi and taken steps, here we are going to describe approach conducted and what was the final output and business benefits.
Frank’s tire catalogue included 80 tire manufacturers and over 20 000 unique tire models, with 5digit number of tires moving daily. Aside from the risk of human error during sorting upon arrival, there was a risk of human error when sorting prior to shipping out.