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Demystifying transfer learning with Tensorflow

In many organizations, a lot of data and work goes into training models in machine learning. The cost of the model training also becomes very high if the model becomes complex. Complex machine learning models can only be made with years of experience and it becomes difficult for Machine learning and AI engineers to make the models more efficiently and quickly. This is where transfer learning comes into the frame to help them. Transfer learning is a machine learning method where a model developed for a task is reused as the starting point for a model on a second task. It is an opportunistic way of reducing machine learning model training to be a better steward of an organization's resources.

Through this video, you will discover how you can use transfer learning to speed up training and improve the performance of your deep learning model.

Presenters:

shubham

Shubham Goyal
Software Consultant at Knoldus Inc.

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