#016 PyTorch - Three hacks for improving the performance of Deep Neural Networks: Transfer Learning, Data Augmentation, and Scheduling the Learning rate in PyTorch

In this post, we are going to talk about very popular deep learning techniques that we can apply to speed up training and improve the performance of our deep learning model. You will learn how you can use transfer learning and some other popular methods like data augmentation and scheduling the learning rate. Transfer learning is an incredibly powerful technique where pre-trained models are used as the starting point on computer vision and natural language processing tasks. So in other words, a network trained for one task is adapted to another task. With transfer learning, you're likely to spend much less time in training.