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I am new to ML and still learning it. My problem is to identify duplicate products. I have a dataset containing product details such as name, colour, size, description, features...
Asked on 12/04/2021
2 answerI have a question about data cleaning. I am a novice and have just started learning in this field so please pardon my ignorance. Suppose there are two columns and...
Asked on 12/04/2021
1 answerI am executing this code which works perfectly for me: (I only have 'positive' and 'negative' sentiments):from sklearn import metricsprint('Accuracy:',metrics.accuracy_score(test_sentiments, predicted_sentiments)) print('Precision:',metrics.precision_score(test_sentiments, predicted_sentiments, pos_label='positive'))My question is: how come...
Asked on 12/04/2021
1 answerI am training an LSTM for time series forecasting and it has produced an extremly high loss value during one epoch:Epoch 00043: saving model to /...904/904 - 2s -...
Asked on 12/02/2021
1 answerI am new to deep learning and I am confused about having a neural network trained on certain classes and tested on different ones. Suppose I want to have a...
Asked on 12/02/2021
2 answerWhen Implementing custom loss function how to make it invariant to the batch size. For example lets say dice loss is being implemented. The formula for dice loss is:...
Asked on 12/02/2021
0 answerHow can get the hidden layer outputs in a simple one-layer lstm?cat("Building Modeln") ...
Asked on 11/30/2021
1 answerI am analysing a technique "Sherlock" - a semantic type of column detecting technique wherein training dataset too many samples of a specific type are limited up...
Asked on 11/30/2021
1 answerI have a dataset on which one of the features has a lot of different categorical values. Trying to use a LabelEncoder, OrdinalEncoder or a OneHotEncoder results in an error,...
Asked on 11/30/2021
3 answerI have been trying to run linear regression with SGD that is found in Spark mllib for some time and I am experiencing huge performance problems. All examples that I...
Asked on 11/27/2021
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