Recent Advances in Machine Learning with Applications to Internet of Things (IoT)
Adam McElhinney, Head of Data Science, Uptake Technologies
The proliferation of sensor technologies has resulted in more connected machines than ever before. This change is resulting in huge quantities of sensor data becoming available for analysis. Machine learning algorithms have resulted in a mixed track record of success with these data sources. Adam gives an overview of the state of machine learning as applied to IoT and industrial equipment. He discusses some of the challenges with current approaches, exciting theoretical advancements and some “lessons learned” from the field.