Hands-On Transfer Learning with Python

Foreword

Chances are you are familiar with the recent and seemingly endless machine learning innovations, but do you know about what goes into training a machine learning model? Generally, a given machine learning model is trained on specific data for a particular task. This training process can be exceptionally resource and time-consuming, and since the resulting models are task-specific, the maximum potential of the resulting model is not realized.

Optimally-performing neural network models, for example, are often the result of many iterations of fine-tuning from researchers or practitioners. Could these trained models not be additionally exploited for a wider assortment of tasks? Transfer learning involves the leveraging of existing machine ...