A personal experience in using Machine Learning, thermography and python to develop a small project that saved over 2000 jobs in the pharmaceutical industry. This talk will highlight how image processing and machine learning was used together to predict failures of critical equipment in a pharmaceutical plant.
You will be taken through the thinking process using scientific principles and how that was translated to code. Furthermore you will be shown code snippets of the formulas translated into code affirming how easy it was to implement the project with less that 100 lines of code.
In conclusion you will learn about the tale of how this project was freely developed, saving money and jobs.
Session author's bio
Co-founder of a non-profit called Zimbopy, an organisation that targets to increase presence of women in technological fields. PSF managing member and DSF member. Currently stays in Zimbabwe working as a Group DevOps Engineer for a global technology company.
|Level of Difficulty||Beginner|