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deep-learning time-series tensorflow cnn lstm-model lstm-neural-networks time-series-forecasting cnn-lstm-models Updated Jan 11, 2022 Jupyter Notebook abhilash1910 / Deep_Reinforcement_Learning_Trading Sponsor Star 23 Code Issues Pull requests Deep Reinforcement Learning for Trading time-series...
learning_rate=0.001training_iters=20batch_size=128display_step=10n_input=28n_step=28n_hidden=128n_classes=10(x_train,y_train),(x_test,y_test)=mnist.load_data()x_train=x_train.reshape(-1,n_step,n_input)x_test=x_test.reshape(-1,n_step,n_input)x_train=x_train.astype('float32'...
importtorchimporttorch.nnasnnimportnumpyasnpimportpandasaspdimportmatplotlib.pyplotaspltfromsklearn.preprocessingimportMinMaxScaler# 检查GPU可用性device=torch.device("cuda"iftorch.cuda.is_available()else"cpu")print(f"Using device:{device}")# 加载数据url="https://raw.githubusercontent.com/jbrownlee/Dat...
xLSTM的新闻大家可能前几天都已经看过了,原作者提出更强的xLSTM,可以将LSTM扩展到数十亿参数规模,我们今天就来将其与原始的lstm进行一个详细的对比,然后再使用Pytorch实现一个简单的xLSTM。 xLSTM xLSTM 是对传统 LSTM 的一种扩展,它通过引入新的门控机制和记忆结构来改进 LSTM,旨在提高 LSTM 在处理大规模数据...
model.compile(loss ='categorical_crossentropy', optimizer='adam',metrics =['accuracy'])print(model.summary())现在，我在训练集上训练我的模型，然后在验证集上检验准确率。Y = pd.get_dummies(data['sentiment']).values X_train, X_valid, Y_train, Y_valid = train_test_split(X,Y, test_size ...
1. model = Sequential() 2. model.add(LSTM(300, input_shape=(maxlen, len(chars)), return_sequences=True, dropout=.20, recurrent_dropout=.20)) 3. model.add(LSTM(300, return_sequences=True, dropout=.20, recurrent_dropout=.20)) 4. model.add(LSTM(300, dropout=.20, recurren...
langdata_lstm:https://github.com/tesseract-ocr/langdata_lstm 文本编辑器:我使用的是notepad++(这个按个人使用的习惯,没有要求),还要用到cmd或者Power Shell,另外jTessBoxEditor这个工具也可下载(需要Java环境),虽然本例子中并不需要jTessBoxEditor,但是可用它打开图片+box文件看看。
## 本项目完整代码：github.com/aialgorithm/Blog # 或“算法进阶”公众号文末阅读原文可见 model =...
batch_first=True)self.fc=nn.Linear(hidden_size,output_size)defforward(self,x):out,_=self.lstm(x)out=self.fc(out[:,-1,:])# 只取最后一个时间步的输出returnout# 创建模型实例input_size=1# 特征数量hidden_size=50# 隐藏层单元数量output_size=1# 预测结果数量model=LSTMModel(input_size,hidden...