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You are a helpful chatbot that always answers in Uzbek.<|eot_id|><|start_header_id|>user<|end_header_id|>

CSV faylidan SMILES yoki SMARTS qatorlari ro'yxatini yuklash uchun python skriptini yozing. Kirish ma'lumotlarini tozalang va har qanday takrorlangan yoki tautomerlarni olib tashlang. Barcha protonatsiya holatlari pH 7 uchun mos ekanligiga ishonch hosil qiling. CSV faylida topilgan yorliqni taxmin qilish uchun kichik LSTM yarating.<|eot_id|><|start_header_id|>assistant<|end_header_id|>

Quyidagi qadamlarning asosiy ko'rinishi: CSV faylini o'qing va SMILES / SMARTS qatorlari va yorliqlarini chiqarib oling SMILES / SMARTS qatorlarini RDKit yordamida tozalang - takrorlanganlarni olib tashlang, tautomerlar / protomerlarni standartlashtiring va boshqalar LSTM modelini yarating Tozalangan ma'lumotlarga asoslanib modelni o'rgating Modellning ishlashini baholang Shunday qilib, kodda u quyidagicha ko'rinadi: import pandas as pd from rdkit import from sklearn.model_selection train import_test_split from keras.models import Sequential from keras.layers import LSTM, Dense # CSV o'qing va ma'lumotlarni chiqarib oling df = pd.read_csv' (((data.vcs') smiles = df['SMILES'<|eot_id|><|start_header_id|>user<|end_header_id|>

Kodni Go yoki Rustga aylantira olasizmi?<|eot_id|><|start_header_id|>assistant<|end_header_id|>

Men ikkalasi bilan ham xursandman. Keling, Rust: ``rust extern crate pandas; extern crate rdkit; extern crate sklearn; extern crate keras; use pandas::pandas::read_csv; use rdkit::rdkit::{Chem, MolToSmiles, MolFromSmiles}; use sklearn::model_selection::train_test_split; use keras::models::Sequential; use keras::layers::{LSTM, Dense}; // CSV faylidan ma'lumotlarni o'qing / yuklab oling / yuklab oling; let_test_in_extern_hub.com; let_test_in_extern_hub.com; let_test_in_extern_hub.com; let_test_in_extern_web.com; let_test<|eot_id|>