From | DataWhale Training techniques are very important for deep learning. As a highly experimental science, even the same network architecture trained with different methods can yield significantly different results. Here, I summarize my experiences from the past year and share them with everyone. I also welcome additions and corrections. Parameter Initialization Any of the … Read more
Click on the “Datawhalee” above to select the “Starred“ public account Get valuable content at the first time Training techniques are very important for deep learning. As a highly experimental science, using different training methods on the same network structure can yield significantly different results. Here, I summarize my experiences from the past year and … Read more
Author: Jeremy Jordan Translation by Machine Heart Contributors: Huang Xiaotian, Xu Di Every machine learning researcher faces the challenge of hyperparameter tuning, and during this tuning process, the adjustment of the learning rate is a crucial part. The learning rate represents the speed at which information accumulates over time in a neural network. Ideally, we … Read more