๐ ๐๐ฉ๐จ๐๐ก ๐ฏ๐ฌ ๐๐ญ๐๐ซ๐๐ญ๐ข๐จ๐ง ๐ข๐ง ๐๐๐๐ฉ ๐๐๐๐ซ๐ง๐ข๐ง๐ โ ๐๐ก๐ ๐๐จ๐ฌ๐ญ ๐๐จ๐ฆ๐ฆ๐จ๐ง๐ฅ๐ฒ ๐๐จ๐ง๐๐ฎ๐ฌ๐๐ ๐๐๐ซ๐ฆ๐ฌ!
When training a neural network, two words confuse most beginners:
๐น ๐๐ฉ๐จ๐๐ก
๐๐ฏ ๐ฆ๐ฑ๐ฐ๐ค๐ฉ ๐ฎ๐ฆ๐ข๐ฏ๐ด ๐ต๐ฉ๐ฆ ๐ฎ๐ฐ๐ฅ๐ฆ๐ญ ๐ฉ๐ข๐ด ๐ด๐ฆ๐ฆ๐ฏ ๐ต๐ฉ๐ฆ ๐ฆ๐ฏ๐ต๐ช๐ณ๐ฆ ๐ฅ๐ข๐ต๐ข๐ด๐ฆ๐ต ๐ฐ๐ฏ๐ค๐ฆ.
๐๐ง ๐บ๐ฐ๐ถ ๐ต๐ณ๐ข๐ช๐ฏ ๐ง๐ฐ๐ณ 10 ๐ฆ๐ฑ๐ฐ๐ค๐ฉ๐ด, ๐บ๐ฐ๐ถ๐ณ ๐ฎ๐ฐ๐ฅ๐ฆ๐ญ ๐จ๐ฐ๐ฆ๐ด ๐ต๐ฉ๐ณ๐ฐ๐ถ๐จ๐ฉ ๐ต๐ฉ๐ฆ ๐ธ๐ฉ๐ฐ๐ญ๐ฆ ๐ฅ๐ข๐ต๐ข 10 ๐ต๐ช๐ฎ๐ฆ๐ด.
๐น ๐๐ญ๐๐ซ๐๐ญ๐ข๐จ๐ง
๐๐ฏ ๐ช๐ต๐ฆ๐ณ๐ข๐ต๐ช๐ฐ๐ฏ ๐ช๐ด ๐ฐ๐ฏ๐ฆ ๐ธ๐ฆ๐ช๐จ๐ฉ๐ต ๐ถ๐ฑ๐ฅ๐ข๐ต๐ฆ, ๐ฃ๐ข๐ด๐ฆ๐ฅ ๐ฐ๐ฏ ๐ข ๐ด๐ช๐ฏ๐จ๐ญ๐ฆ ๐ฃ๐ข๐ต๐ค๐ฉ ๐ฐ๐ง ๐ฅ๐ข๐ต๐ข.
If you have:
10,000 ๐ณ๐ฆ๐ค๐ฐ๐ณ๐ฅ๐ด
๐๐ข๐ต๐ค๐ฉ ๐ด๐ช๐ป๐ฆ = 100
๐ ๐๐ฉ๐ฆ๐ฏ ๐บ๐ฐ๐ถ ๐จ๐ฆ๐ต 100 ๐ช๐ต๐ฆ๐ณ๐ข๐ต๐ช๐ฐ๐ฏ๐ด ๐ฑ๐ฆ๐ณ ๐ฆ๐ฑ๐ฐ๐ค๐ฉ.
โ๏ธ ๐๐ข๐ฆ๐ฉ๐ฅ๐ ๐๐ง๐๐ฅ๐จ๐ ๐ฒ
๐๐ก๐ข๐ง๐ค ๐จ๐ ๐ ๐จ๐ข๐ง๐ ๐ญ๐จ ๐ญ๐ก๐ ๐ ๐ฒ๐ฆ:
๐๐ฉ๐จ๐๐ก = ๐๐จ๐ฆ๐ฉ๐ฅ๐๐ญ๐ข๐ง๐ ๐ญ๐ก๐ ๐๐ง๐ญ๐ข๐ซ๐ ๐ฐ๐จ๐ซ๐ค๐จ๐ฎ๐ญ ๐ฉ๐ฅ๐๐ง ๐จ๐ง๐๐
๐๐ญ๐๐ซ๐๐ญ๐ข๐จ๐ง = ๐๐จ๐ข๐ง๐ ๐จ๐ง๐ ๐ฌ๐๐ญ ๐ข๐ง๐ฌ๐ข๐๐ ๐ญ๐ก๐๐ญ ๐ฐ๐จ๐ซ๐ค๐จ๐ฎ๐ญ
The model becomes stronger with every iteration, and improves overall with more epochs.
Read More: https://telegra.ph/Demystifying-Epochs--Iterations-in-Deep-Learning-11-24
๐ @codeprogrammer
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