- Deep Learning with Keras
- Antonio Gulli Sujit Pal
- 84字
- 2021-07-02 23:58:05
Increasing the number of epochs
Let's make another attempt and increase the number of epochs used for training from 20 to 200. Unfortunately, this choice increases our computation time by 10, but it gives us no gain. The experiment is unsuccessful, but we have learned that if we spend more time learning, we will not necessarily improve. Learning is more about adopting smart techniques and not necessarily about the time spent in computations. Let's keep track of our sixth variant in the following graph:

推薦閱讀
- Intel FPGA/CPLD設(shè)計(jì)(基礎(chǔ)篇)
- 筆記本電腦使用、維護(hù)與故障排除實(shí)戰(zhàn)
- 精選單片機(jī)設(shè)計(jì)與制作30例(第2版)
- 電腦維護(hù)365問
- 計(jì)算機(jī)組裝與維修技術(shù)
- Large Scale Machine Learning with Python
- Hands-On Artificial Intelligence for Banking
- LPC1100系列處理器原理及應(yīng)用
- WebGL Hotshot
- FreeSWITCH Cookbook
- 觸摸屏應(yīng)用技術(shù)從入門到精通
- 嵌入式系統(tǒng)原理及應(yīng)用:基于ARM Cortex-M4體系結(jié)構(gòu)
- USB應(yīng)用開發(fā)寶典
- Drupal Rules How-to
- 創(chuàng)客電子:Arduino和Raspberry Pi智能制作項(xiàng)目精選