I have been trying to build a RandomForestClassifier() (RF) model and a DecisionTreeClassifier() (DT) model in order to get the same output (only for learning p
While we create a pycaret setup, e.g.: from pycaret.regression import all exp_reg101 = setup(data = data, target = 'Price', session_id=123,preprocess=False) I
I have been trying to do image augmentation using a library called Albumentations. But I got some error from OpenCV while transforming the images. I ran the cod
I have an array of tensors for a single image. I want to flatten the vectors and perform PCA on the same. The below is the code to extract the tensors on a sing
I am trying to use Tensorflow and Keras for a prediction model. I first read in my dataset that has shape (7709, 58), then normalize it: normalizer = tf.keras.l
I am working on a trainning task with CNN. When I created the loss function with CrossEntropyLoss and trained the dataset, the error reminded me that the batch
I'm trying to do polynomial regression using this code here: x_train,x_test,y_train,y_test = train_test_split(self.X, self.y, test_size=split, random_state=rand
I am trying to reproduce my code from online Jupyter Notebook (COURSERA) to my own local environment （Anaconda 3 Jupyter with CUDA installed) All Codes a
I have two datasets that are collected at different frequencies at the same time. One is recorded at 128Hz and another one is recorded at 512 Hz. I am trying to
How can I make this DNN model in tensorflow? 31 neurons in the first, 10 in the second, 5 in the third hidden layer, and 2 neurons in the output layer. The acti
When working with scaled data, dummy variables should also be scaled or should be left apart without scaling? Can ML algorithms produce different result and whi
I am using CNN-LSTM network for image classification. My image size is (224, 224, 3) and batch size is 90. I m getting this error when i passing input to LSTM l
I want to use ensemble model by stacking Multiple Linear Regression, SVR, Decision Tree Regression and ANN regression. How can I do that?
I have developed a model with three inputs types. Image, categorical data and numerical data. For Image data I've used ResNet50 for the other two I develop my o
I am trying to classify between drones and birds using machine learning. I have got a big number of samples of feature vectors from a radar which generally con
My weights and biases (wandb) panels (e.g. for loss) shortly show line plots (x: steps, y: loss), then refresh (showing a spinner for some time) and then only s
I want to convert this below RNN into bidirectional RNN, how can I do that? #Call the function and compile the model. model = RNN() model.summary() model.compil
I am dealing with a binary classification problem that feeds a network with two inputs (images), model_vgg16_conv = VGG16(weights='imagenet', include_top=False)
import pandas as pd from sklearn.feature_extraction.text import TfidfTransformer from sklearn.feature_extraction.text import TfidfVectorizer import path import
We are trying to deploy a model to Azure ML workspace containing a saved model & One Hot Encoded joblib file. We are facing issue in init(