I'm attempting to do a grid search to optimize my model but it's taking far too long to execute. My total dataset is only about 15,000 observations with about 30-40 variables. I was successfully ab...

I want to create a L2 loss function that ignores values (=> pixels) where the label has the value 0. The tensor batch[1] contains the labels while output is a tensor for the net output, both have a...

I am trying to implement a detection model based on "finetuning object detection" official tutorial of PyTorch. It seemed to have worked with minimal data, (for 10 of images). However I uploaded m...

As I understand it, in a deep neural network, we use an activation function (g) after applying the weights (w) and bias(b) (z := w * X + b | a := g(z)). So there is a composition function of (g o z...

I was reading the papers on deep learning. Most of them refer to unsupervised learning. They also say the neurons are pre-trained using unsupervised RBM network. Later they are fine tuned us...

For example: If I want to train a classifier (maybe SVM), how many sample do I need to collect? Is there a measure method for this?

I am trying in Amazon Sagemaker to deploy an existing Scikit-Learn model. So a model that wasn't trained on SageMaker, but locally on my machine. On my local (windows) machine I've saved my model a...

I am trying to implement bag of word model from kaggle site with a twitter sentiments data which has around 1M raw. I already clean it but in last part when I applied my features vectors and sentim...

I have 7 classes and the total number of records are 115 and I wanted to run Random Forest model over this data. But as the data is not enough to get a high accuracy. So i wanted to apply oversampl...

I am designing a neural network and am trying to determine if I should write it in such a way that each neuron is its own 'process' in Erlang, or if I should just go with C++ and run a networ...

I'm trying to implement a multiclass logistic regression classifier that distinguishes between k different classes. This is my code. import numpy as np from scipy.special import expit def cost(...

How do we make sense of SHAP explainer.expected_value? Why is it not the same with y_train.mean() after sigmoid transformation? Below is a summary of the code for quick reference. Full code availab...

Theres not that much information given in the TensorFlow documentation: https://www.tensorflow.org/api_docs/python/tf/train/Example https://www.tensorflow.org/api_docs/python/tf/train/SequenceExamp...

Below the code import numpy as np np.random.seed(0) from sklearn import datasets import matplotlib.pyplot as plt %matplotlib inline %config InlineBackend.figure_format ='retina' from keras.models ...

I am training an OCR model for recognizing MRZ from passport. To train my model for more accuracy, I need to train it with maximum pictures possible. I tried to find passport's dataset on KAGGLE bu...

I am working on Multiclass Classification (4 classes) for Language Task and I am using the BERT model for classification task. I am following this blog post Transfer Learning for NLP: Fine-Tuning B...

In scikit-learn, some clustering algorithms have both predict(X) and fit_predict(X) methods, like KMeans and MeanShift, while others only have the latter, like SpectralClustering. According to the ...

I tried to run the code below, taken from CS50's AI course: import csv import tensorflow as tf from sklearn.model_selection import train_test_split # Read data in from file with open("banknot...

I use this notebook from Kaggle to run LSTM neural network. I had started training of neural network and I saw that it is too slow. It is almost three times slower than CPU training. CPU perfoma...

I want to implement a custom loss function in scikit learn. I use the following code snippet: def my_custom_loss_func(y_true,y_pred): diff3=max((abs(y_true-y_pred))*y_true) return diff3 score=m...

I'm following some lectures from lynda.com about deep learning using Keras-TensorFlow in a PyCharmCE enviroment and they didn't have this problem. I get this error: raise ImportError('Could not im...

I got this from the sklearn webpage: Pipeline: Pipeline of transforms with a final estimator Make_pipeline: Construct a Pipeline from the given estimators. This is a shorthand for the Pipeline co...

I understand that random_state is used in various sklearn algorithms to break tie between different predictors (trees) with same metric value (say for example in GradientBoosting). But the document...

I have an issue with tf.callbacks.ModelChekpoint. As you can see in my log file, the warning comes always before the last iteration where the val_acc is calculated. Therefore, Modelcheckpoint never...

I am having hard time understanding position wise feed forward neural network in transformers architecture. Lets take example as Machine translation task, where inputs are sentences. From the figu...