I am working on an image classification task to classify among cars and buses. The problem is that in most car images, there is buses in the background and vice
I am trying to use Tensorflow to create a recommendation system. What I want to do is to read data from two csv files, one containing 'item_id' and the other co
I've loaded in my train and validation sets from CIFAR10 like so: train = tfds.load('cifar10', split='train[:90%]', shuffle_files=True) validation = tfds.load('
For a very simple classification problem where I have a target vector [0,0,0,....0] and a prediction vector [0,0.1,0.2,....1] would cross-entropy loss converge
I am currently using a dataset of over 2.5 million images, of which I use the image itself as a comparison to eachother, for use in a content-based recommendati
I have two google accounts each one contains part of my data and i can,t include the data into one drive because of the size limit. So, I want to know if there
I'm using the gradio library with one of the basic examples, but am getting this error. I am running this in a Google Colab Notebook. Here is the relevant lines
I know that it can be loaded using tfds.load('nyu_depth_v2') and I have try it but it fails I suspect due to my slow internet connection I have downloaded the d
I am working with Azure Databricks jupyter notebooks and have time-consuming jobs (complex queries, model training, loops over many items, etc.). Every time I c
I am trying to build the following model but am getting this error when I am finally training the model and trying to get it's accuracy. It gets stuck when I am
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
I've been using sklearn's random forest, and I've tried to compare several models. Then I noticed that random-forest is giving different results even with the s
I ran PCA on a data frame with 10 features using this simple code: pca = PCA() fit = pca.fit(dfPca) The result of pca.explained_variance_ratio_ shows: array
I try to transfer learn a LightningModule. The relevant part of the code is this: class DeepFilteringTransferLearning(pl.LightningModule): def __init__(self
In the following code I have defined a Sequential model, that contains two parts conv_encoder and conv_decoder. After training the model I want to use conv_enco
When I run classifier.py in the openface demos directory using: classifier.py train ./generated-embeddings/ I get the following error message: --> fro
I am trying to use SMOTE in python to handle highly imbalanced data set. After splitting the data set into train and test I generate synthetic samples using SMO
I am trying to convert some code from tensorflow 1.x to tensorflow 2.x. It's been going well so far, but I'm stuck on atrous convolution. Unlike other layers, t
I am trying to develop a GAN, I have created the generator and the discriminator and now I am trying to train it. I am using the Mnist dataset but I plan to use
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