Transfer Learning Using Teachable Machine For Classification Of Glassware In Chemistry Lab

Image classification is an important use case of deep learning algorithms. Convolution Nural networks, CNNs, have evolved to an extent where pretrained models can be used to train new models. The technique used for this type of model building activity is called as Transfer lerning. We have developed an image classification model using transfer lerning to classify lab glassware used in Chemistry lab. This model can be used for training purpose for the students in high schools who are not much aware about the practical implementation of laboratory experiments. We have used subset of Labpics dataset developed by Eppel et.al. We have used teachable machine as a platform to build this model with very limited computational resource. With transfer learning mechanism used by teachable machine platform we were able to achieve ~83% accurate image classification model