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Consider a simplified Recurrent Neural Network (RNN) with a single input and a single output. The hidden state is updated using the recurrence:$$ h_t = \text{ReLU}(W_{ih}...
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For the following neural network, calculate accuracy of classification, given these settings
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Hello,I have a dataset with a categorical column that contains three categories. One of the categories represents 98% of the data, while the remaining 2% are distributed ...
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When pre processing data for machine learning. Is there any difference in using one hot encoding to turn categoric variables into numeric variables or to segment the data...
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Given the following sample dataset with 5 samples and 2 features:SampleFeature 1Feature 2Actual ValuePredicted Value1234623456345674567856789Calculate the residual errors...
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I have some skepticism about the validity of the charts below comparing the critic and audience reviews for Phase 4 of the MCU to the previous 3 phases. There are over 18...
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Provide a short list of free cloud labs on Qwiklabs
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# for key, value in dict.items(): # if value >= long: # long = value # long_name = key # if value < sh...
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I am trying to extract information such as profits, revenues and others along with their corresponding dates and quarters from an unstructured text about stock market and...
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How do I accurately compare between the number of something a survey measure from my employees each year with a varying umber of survey engagement and employee size?If I ...
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Is it possible to make a forecast of a future value of Air Temperature using Fast Fourier Transform, if yes, what should be the process or how you'll be able to do it. Th...
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Input is a stock price in exponential transformation. We are asked to forecast using ARMA results for 2 years.
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I have a dataset with 7 labels in the target variable.X = data.drop('target', axis=1) Y = data['target'] Y.unique()array(['Normal_Weight', 'Overweight_Level_I', 'Overweig...
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Hello everyone newbie data scientist here.I'm working on a project to predict companies (probability of default) bankruptcy probability and to assign them a credit rating...
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I have the code below, outputting the accuracy. How can I output the F1-score instead? Thanks in advance,clf.fit(data_train,target_train) preds = clf.predict(data_test) #...
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from keras.models import Sequential from keras.layers import Dense from keras.layers import LSTM from sklearn.model_selection import train_test_splitmodel = Sequential() ...
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Where can I find projects related to battery data?
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I want to build a dynamic pricing model which means if product is too expansive for a client and there is a risk that we might loose a client we lower the price for them ...
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This would be for a company that is just now looking into using a software to track data for wine making.