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-rasm
3.Google Driveda ishlash va fayllarni boshqarish
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| bet | 4/5 | | Sana | 13.02.2024 | | Hajmi | 1.9 Mb. | | #155359 |
Bog'liq Muhitlar maktabgacha-yoshdagi-bolalarga-ingliz-tilini-o-rgatish-usullari, 1-mavzu, 1-variant 8-B ga 27-may, Beton texnologiyasi 2 qism, tavsifnoma, Maruza 2, bCueCn1je0JZWWqdC5DDGvzeQpnWm1uSqMyVxFIV1.2.18-rasm
3.Google Driveda ishlash va fayllarni boshqarish.
Yaratilgan fayllarni topish uchun Google Drivega o‘tiladi bu sahifaga quyidagi link orqali kirish mumkin https://drive.google.com/drive/my-drive
Google Drivening My Drive bo‘limida Colab Notebooks papkasiga kiriladi.
1.2.19-rasm
Yuqoridagi papkaning ichida yaratilgan barcha .ipynb fayl kengaytmali fayllar saqlanadi shu jumladan First_NB.ipynb fayli ham. Google colabni Google Drive dan ham ishga tushirish mumkin buning uchun kerakli faylning ustiga ikki marta bosish kifoya. Va tanlangan faylni to‘g‘ridan-to‘g‘ri ochish imkoniyati bo‘ladi.
1.2.20-rasm
Google Drivening o‘zida turib ham google colabda yangi fayl yaratish mumkin buning uchun quyidagi ketma-ketlik bajariladi.(1.2.21-rasm)
1.2.21-rasm
Google colabning yana bir afzallik tomoni ko‘plab kutubxonalar oldindan o‘rnatilgan bo‘ladi va doimiy ravishda kutubxonalar versiyasi yangilanib boriladi. Buni tekshirish uchun doimiy foydalaniladigan kutubxonalarni Cellda yuritib ko‘rish orqali ishlashini tekshirish mumkin.
import numpy as np
import pandas as pd
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn.metrics import accuracy_score
from sklearn.metrics import recall_score
from sklearn.metrics import f1_score
from sklearn.metrics import precision_score
from sklearn import tree
from matplotlib import pyplot as plt
from sklearn.model_selection import cross_val_predict
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