Awọn ẹya

1. Ifihan si Imọye Oríkĕ ati Ijẹrisi Ijẹrisi ni Imọ-ẹrọ Agbin 2. Konge Agriculture ati igbekale ti Agricultural Data 3. Abojuto Ilera ọgbin pẹlu Satẹlaiti ati Drone: NDVI ati Awọn itọka Eweko 4. Itumọ Itupalẹ Ilẹ ati Iṣapejuwe Idaji 5. Imudara irigeson ati iṣakoso omi 6. Arun ati Ayẹwo Kokoro: Ayẹwo Aworan ati Ipinnu 7. Atilẹyin Ipinnu Ogbin pẹlu Oju-ọjọ ati Data Oju-ọjọ 8. Iṣiro Ikore ati Awoṣe Agbe 9. Agricultural Data Analysis pẹlu Python 10. Traceability, Iforukọsilẹ Agricultural ati Pq Ipese 11. Ethics, Asiri, Awọn aala ati Isopọpọ Ipari-si-opin

Ẹyọ 9 / 11

Agricultural Data Analysis pẹlu Python

Awọn anfani:

Agbara lati ṣe ipilẹṣẹ ati ṣiṣiṣẹ koodu fun ikojọpọ, mimọ ati akopọ aaye / data sensọ nipa lilo pandas pẹlu AI
Agbara lati wo awọn itupalẹ bii jara akoko NDVI ati ibatan ajile / ikore pẹlu awọn aworan
Agbara lati ṣe idanwo koodu ti ipilẹṣẹ AI pẹlu data kekere ati ri ẹyọkan, agbekalẹ atọka ati awọn aṣiṣe oye

Ti tẹlẹ Itele