Ma’lumotlarni yuklash.
Ta'lim modelini yaratish uchun bizga tashqi dunyoni ifodalovchi ma'lumotlar kerak. Endi bizda kerakli Python paketlari oʻrnatilgan boʻlsa, keling, maʼlumotlar bilan oʻzaro ishlashda ulardan qanday foydalanishni koʻrib chiqamiz. Terminal oynasida quyidagi buyruqni kiritish orqali Python buyruq qatoriga o'tamiz:
$ python3
Barcha ma'lumotlar to'plamini o'z ichiga olgan paketni import qiling.
>>> from sklearn import datasets
Masalan, ko'chmas mulk narxlari bilan ma'lumotlar to'plamini yuklaymiz:
>>> house_prices = datasets.load_boston()
Ma’lumotni ekranga chiqaramiz:
>>> print(house_prices.data)
Ekranda quyidagi ko’rinish paydo bo’ladi:
1-rasm.
3. Laboratoriya ishinibajarish bo’yicha topshiriq.
1). Har bir talaba Windows OT uchun Python3 dasturlash tilini hamda Scikit-learn paketini o’rnatish jarayonini amaliy bajarishi kerak.
2). Laborotoriya ishining keltirilgan adabiyotlar ro’yhatidagi birinchi adabiyotdan foydalanib, pyton dasturida kichik dastur yaratish.
№
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Talabalarning lms.tuit.uz tizimiagi elektron journali bo'yicha Variant raqamlari.
|
Python dasturida o'rganilishi kerak bo’lgan Datasets ro'yhati
|
1.
|
Variant №1
|
load_boston
|
2.
|
Variant №2
|
fetch_20newsgroups
|
3.
|
Variant №3
|
load_breast_cancer
|
4.
|
Variant №4
|
fetch_20newsgroups_vectorized
|
5.
|
Variant №5
|
load_diabetes
|
6.
|
Variant №6
|
fetch_california_housing
|
7.
|
Variant №7
|
load_digits
|
8.
|
Variant №8
|
fetch_covtype
|
9.
|
Variant №9
|
load_files
|
10.
|
Variant №10
|
fetch_kddcup99
|
11.
|
Variant №11
|
load_linnerud
|
12.
|
Variant №12
|
fetch_lfw_pairs
|
13.
|
Variant №13
|
load_sample_image
|
14.
|
Variant №14
|
fetch_lfw_people
|
15.
|
Variant №15
|
load_svmlight_file
|
16.
|
Variant №16
|
fetch_openml
|
17.
|
Variant №17
|
load_wine
|
18.
|
Variant №18
|
fetch_rcv1
|
19.
|
Variant №19
|
load_boston
|
20.
|
Variant №20
|
fetch_species_distributions
|
21.
|
Variant №21
|
load_digits
|
22.
|
Variant №22
|
fetch_olivetti_faces
|
23.
|
Variant №23
|
load_breast_cancer
|
24.
|
Variant №24
|
fetch_20newsgroups_vectorized
|
25.
|
Variant №25
|
load_diabetes
|
4. Adabiyotlar ro’yxati.
1. Джоши, Пратик. Искусственный интеллект с примерами на Python. : Пер. с англ. - см. : 000 ”Диалектика”, 2019. — 448 с.
2. Dipanjan Sarkar, Raghav Bali, Tushar Sharma. Practical Machine Learning with Python.
3. Том Таулли. Основы искусственного интеллекта: нетехническое введение
2021
4. https://scikit-learn.org/stable/install.html
№
|
Talabalarning lms.tuit.uz tizimiagi elektron journali bo'yicha Variant raqamlari.
|
Python dasturida o'rganilishi kerak bo’lgan Datasets ro'yhati
|
1.
|
Variant №1
|
load_boston
|
2.
|
Variant №2
|
fetch_20newsgroups
|
3.
|
Variant №3
|
load_breast_cancer
|
4.
|
Variant №4
|
fetch_20newsgroups_vectorized
|
5.
|
Variant №5
|
load_diabetes
|
6.
|
Variant №6
|
fetch_california_housing
|
7.
|
Variant №7
|
load_digits
|
8.
|
Variant №8
|
fetch_covtype
|
9.
|
Variant №9
|
load_files
|
10.
|
Variant №10
|
fetch_kddcup99
|
11.
|
Variant №11
|
load_linnerud
|
12.
|
Variant №12
|
fetch_lfw_pairs
|
13.
|
Variant №13
|
load_sample_image
|
14.
|
Variant №14
|
fetch_lfw_people
|
15.
|
Variant №15
|
load_svmlight_file
|
16.
|
Variant №16
|
fetch_openml
|
17.
|
Variant №17
|
load_wine
|
18.
|
Variant №18
|
fetch_rcv1
|
19.
|
Variant №19
|
load_boston
|
20.
|
Variant №20
|
fetch_species_distributions
|
21.
|
Variant №21
|
load_digits
|
22.
|
Variant №22
|
fetch_olivetti_faces
|
23.
|
Variant №23
|
load_breast_cancer
|
24.
|
Variant №24
|
fetch_20newsgroups_vectorized
|
25.
|
Variant №25
|
load_diabetes
|
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