Sun’iy intelekt texnologiyasining qoʻllanilishi va uni Python dasturlash tili asosida modellashtirish. Ishdan maqsad

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.

№	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