Dev11 Winform Chart Histodiagram을 개발에 이용하려함.https://livecharts.dev/#frameworks LiveCharts - LiveCharts2Beautiful, animated, mv* friendly, automatically updated, cross-platform and easy to use CHARTS 📈, MAPS 🌎 AND GAUGES 🌡️ FOR .NET LiveCharts is a data visualization library for .Net that can run across multiple devices and frameworks, It runs undlivecharts.devhttps://github.com/beto-rodriguez/LiveCharts2 GitHub .. 2024. 6. 22. TensorFlow 2.x - Simple learning import pandas as pd import tensorflow as tf from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense # 데이터 불러오기 및 전처리 data = pd.read_csv('gpascore.csv') data.dropna(inplace=True) y_data = data['admin'].values x_data = data[['gre', 'gpa', 'rank']].values # 신경망 모델 구성 model = Sequential([ Dense(64, activation='tanh', input_shape=(3,)), # 입력 레이어, 입력 노드 3개 (gre, gpa, r.. 2024. 1. 26. Pytorch-Simple learning import pandas as pd import torch import torch.nn as nn import torch.optim as optim from torch.utils.data import DataLoader, TensorDataset # 데이터 불러오기 및 전처리 data = pd.read_csv('gpascore.csv') data = data.dropna() y_data = data['admin'].values x_data = [] for _, row in data.iterrows(): x_data.append([row['gre'], row['gpa'], row['rank']]) # 텐서로 변환 x_tensor = torch.FloatTensor(x_data) y_tensor = torc.. 2024. 1. 26. Keras-simple deep learning 기본적인 사용법의 샘플 import pandas as pd data = pd.read_csv('gpascore.csv') #data.isnull().sum() #빈간갯수? #data.fillna(100)#빈칸을 100을줌 #print(#data['gpa']) #열의값 #print(#data['gpa'].min()) #열의 최저값 #print(#data['gpa'].count()) #열의 갯수 data.dropna()#빈칸, na를 정리해줌 y데이터=data['admin'].values#y=정답 x데이터=[] #x=입력값 배열선언 for i, rows in data.iterrow(): #한 행씩 x데이터.append([rows['gre'],rows['gpa'],rows['rank']])# 추가 [640,1.. 2024. 1. 23. 이전 1 2 3 다음
