By Π₯ΠΎΠ²Π°ΡΠ΄ ΠΠΆΠ΅ΡΠ΅ΠΌΠΈ, Π‘ΠΈΠ»ΡΠ²Π΅ΠΉΠ½ ΠΡΠ³Π³Π΅Ρ
Π₯ΠΎΠ²Π°ΡΠ΄ ΠΠΆΠ΅ΡΠ΅ΠΌΠΈ, Π‘ΠΈΠ»ΡΠ²Π΅ΠΉΠ½ ΠΡΠ³Π³Π΅Ρ, 2022
ΠΡΠ° ΠΊΠ½ΠΈΠ³Π° ΡΠ°Π·ΡΡΡΠ°Π΅Ρ ΡΡΠ΅ΡΠ΅ΠΎΡΠΈΠΏΡ ΠΎ ΡΠ»ΠΎΠΆΠ½ΠΎΡΡΠΈ Π³Π»ΡΠ±ΠΎΠΊΠΎΠ³ΠΎ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ. ΠΠ½Π° ΠΏΠΎΠΊΠ°Π·ΡΠ²Π°Π΅Ρ, ΡΡΠΎ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠΈΡΡΡ, Π·Π½Π°ΠΊΠΎΠΌΡΠ΅ Ρ Python, ΠΌΠΎΠ³ΡΡ Π΄ΠΎΡΡΠΈΠ³Π°ΡΡ Π²ΠΏΠ΅ΡΠ°ΡΠ»ΡΡΡΠΈΡ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ², ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ Π±ΠΈΠ±Π»ΠΈΠΎΡΠ΅ΠΊΡ fastai. Fastai ΠΏΡΠ΅Π΄ΠΎΡΡΠ°Π²Π»ΡΠ΅Ρ ΡΠ΄ΠΎΠ±Π½ΡΠΉ ΠΈΠ½ΡΠ΅ΡΡΠ΅ΠΉΡ Π΄Π»Ρ ΡΠ΅ΡΠ΅Π½ΠΈΡ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½Π½ΡΡ Π·Π°Π΄Π°Ρ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ. ΠΠ²ΡΠΎΡΡ Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΡΡΡ, ΠΊΠ°ΠΊ ΡΠΎΠ·Π΄Π°Π²Π°ΡΡ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠ΅ ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΡ Π±ΡΡΡΡΠΎ, ΠΈΠ·Π±Π΅Π³Π°Ρ ΠΈΠ·Π±ΡΡΠΎΡΠ½ΠΎΠΉ ΡΠ΅ΠΎΡΠΈΠΈ ΠΈ ΡΠ»ΠΎΠΆΠ½ΡΡ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ Π²ΡΠΊΠ»Π°Π΄ΠΎΠΊ. ΠΡΠ½ΠΎΠ²Π½ΠΎΠΉ ΡΠΏΠΎΡ Π΄Π΅Π»Π°Π΅ΡΡΡ Π½Π° ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ.
Jeremy Howard, Sylvain Gugger, 2022
This book challenges the notion that deep learning is exclusively for advanced mathematicians. It demonstrates how any programmer familiar with Python can achieve significant results. The fastai library offers a user-friendly interface for tackling common machine learning tasks. The authors prove that cutting-edge applications can be built rapidly, without getting bogged down in tedious theoretical explanations or complex formulas. The focus is on practical implementation and efficiency.