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How many instances are there in Fashion-MNIST Test dataset ?
30000
10000
20000
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1 End to End ML Project - Fashion MNIST - Description
2 End to End ML Project - Fashion MNIST - Importing Libraries
3 End to End ML Project - Fashion MNIST - Defining Functions
4 End to End ML Project - Fashion MNIST - Loading the data
5 End to End ML Project - Fashion MNIST - How many instances are there in Fashion-MNIST Training dataset ?
6 End to End ML Project - Fashion MNIST - How many instances are there in Fashion-MNIST Test dataset ?
7 End to End ML Project - Fashion MNIST - How many features are there in Fashion-MNIST Training dataset ?
8 End to End ML Project - Fashion MNIST - Understanding the data
9 End to End ML Project - Fashion MNIST - Data Preparation
10 End to End ML Project - Fashion MNIST - Training the Model
11 End to End ML Project - Fashion MNIST - Training the Model - Softmax Regression
12 End to End ML Project - Fashion MNIST - Training the Model - RandomForestClassifier
13 End to End ML Project - Fashion MNIST - In training phase, why would the scores(accuracy, precision, etc.) of any model be 1.0?
14 End to End ML Project - Fashion MNIST - Selecting the Model - Cross-Validation
15 End to End ML Project - Fashion MNIST - Selecting the Model - Cross-Validation - Softmax Regression
16 End to End ML Project - Fashion MNIST - Selecting the Model - Cross-Validation - RandomForestClassifier
17 End to End ML Project - Fashion MNIST - Fine-Tuning the Model - Grid Search - Dimensionality Reduction
18 End to End ML Project - Fashion MNIST - Fine-Tuning the Model - Grid Search - Tuning Hyperparameters
19 End to End ML Project - Fashion MNIST - What is the best parameter value of max_depth parameter you got from the grid search ?
20 End to End ML Project - Fashion MNIST - Evaluating Final Model on Test Dataset
21 End to End ML Project - Fashion MNIST - Which function of PCA do you use to apply dimensionality reduction on test dataset X_test ?
22 End to End ML Project - Fashion MNIST - How many features are there in X_test_reduced dataset ?
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