I am using a faster rcnn model to predict one object in an image. There can only be one object in each image. Is it possible to force Faster Rcnn to train and p
I am training my neural network built with PyTorch under Google Colab Pro+ (Tesla P100-PCIE GPU) but encounters the following strange phenomenon: The amount of
cfg.optimizer.lr = 0.02 / 8 cfg.lr_config.warmup = None cfg.log_config.interval = 600 # Change the evaluation metric since we use customized dataset. cfg.evalua
I am building a MLP using TensorFlow 2.0. I am plotting the learning curve and also using keras.evaluate on both training and test data to see how well it perfo
I am parametrizing the number of hidden layers of a simple ANN using nn.ModuleList. I am wondering if passing this list into a nn.Sequential module as follows w
I've been trying to plot the decision boundary of my neural network which I used for binary classification with the sigmoid function in the output layer but wit
I trained my network several times and I already got some results. Then I found out about the Keras tuner and wanted to find the best hyperparameters with it. b
import pandas as pd import numpy as np from sklearn.preprocessing import StandardScaler from keras import Sequential from tensorflow.keras.layers import Dense f
It is required to resample audio signals within a custom model structure. This resampling task is not a kind of pre/post-processing operation that can be develo
I'm trying to train LSTM model in Keras using data of variable timestep, for example, the data looks like: <tf.RaggedTensor [[[0.0, 0.0, 0.0, 0.0, 0.0, 1.0,
I am trying to train a Deep Neural Network using MNIST data set. BATCH_SIZE = 100 train_data = train_data.batch(BATCH_SIZE) validation_data = validation_data.b
How to change the activation layer of a Pytorch pretrained network? Here is my code : print("All modules") for child in net.children(): if isinstance(chi
I want to use keras to build a neural network regression model from X_train -> Y_train. In this example, however, I need to perform a preprocessing transform
I want to use matrix multiplication inside TF model. My model is a NN with input shape = (1,9). And I want to get a product of this vectors by themself (i.e. I
I have a model, for which i need to compute the gradients of output w.r.t the model's input. But I want to apply some custom gradients for some of the nonlinear
I have written a basic program to understand what's happening in MLP classifier? from sklearn.neural_network import MLPClassifier data: a dataset of body met
is it possible to create my own object detection script with YOLO or create a Neuron Network to implement it in the NAO robot( iknow that there is a box of det
is it possible to create my own object detection script with YOLO or create a Neuron Network to implement it in the NAO robot( iknow that there is a box of det
I am trying to create a copy of a nn.Sequential network. For example, the following is the easiest way to do the same- net = nn.Sequential( nn.Conv2d(16
Suppose, the following is a dataset for solving a regression problem: H -9.118 5.488 5.166 4.852 5.164 4.943 8.103 -9.152 7.470 6.452 6.069 6