Batchsize Effect

The batch size is an important hyperparameter in deep learning that affects both the training time and the accuracy of the model. Here are some resources on the batch size effect in deep learning:

• This video by Siraj Raval on YouTube explains the concept of batch size in deep learning and how it affects the training process:
• This article by TensorFlow provides a detailed explanation of the batch size effect on training time and model accuracy:
• This research paper by Keskar et al. investigates the effect of batch size on the generalization performance of deep neural networks:
• This blog post by Jason Brownlee provides practical tips for choosing an appropriate batch size in deep learning:
• This video by Andrew Ng on YouTube discusses the trade-off between batch size and model accuracy in deep learning: