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SAP Machine Learning Challenge Please read the following instructions carefully Which Novel Do I Belong To? In this challenge, you are tasked with training a machine learning model that classifies a given line of text as belonging to one of the following 12 novels: 0. alice_in_wonderland 1. dracula 2. dubliners 3. great_expectations 4. hard_times 5. huckleberry_finn 6. les_miserable 7. moby_dick 8. oliver_twist 9. peter_pan 10. tale_of_two_cities 11. tom_sawyer You are provided with a zip file (offline_challenge.zip) containing three text files: xtrain.txt ytrain.txt xtest.txt. As you can see in the train files, we have applied an encoding to the text, but it is done such that each character has a deterministic mapping. Each line in xtrain.txt corresponds to a label in ytrain.txt. Example: line: satwamuluhqgulamlrmvezuhqvkrpmletwulcitwskuhlemvtwamuluhiwiwenuhlrvimvqvkruh ulenamuluhqgqvtwvimviwuhtwamuluhulqvkrenamcitwuhvipmpmqvuhskiwkrpmdfuhlrvimv skvikrpmqvuhskmvgzenleuhqvmvamuluhulenamuluhqvletwtwvipmpmgzleenamuhtwamuluh twletwdfuhiwkrxeleentwxeuhpmqvuhtwiwmvamdfuhpkeztwamuluhvimvuhqvtwmkpmpmlelr uhgztwtwskuhtwlrkrpmlruhpmuluhqvenuhtwyplepmxeuhenuhamypkrqvuhamulmvdfuhqvsk entwamletwlrlrpmiwuhtwamul label: 7 Your Task You are tasked with developing a deep learning model that predicts the novel id of a given line of text. We prefer Python as the programming language and TensorFlow/Keras as the deep learning framework. Submission As part of your submission, please include: Your model's predictions on xtest.txt (in the same format as ytrain.txt). This file must be named as ytest.txt Source code as a .zip file (we prefer Jupyter notebooks, size limit is 10 MB) Evaluation Your submission will be evaluated based on the following criteria: Test set accuracy (80%) Explanation/documentation (10%) Implementation (10%) Contents of Source Code In your source code, please include the following: Implementation of the model Clear documentation of relevant parts of the code Training & validation accuracies Explanation of strategy, methodology, and algorithms employed The last point is especially important, as we want to assess your reasoning and approach to this problem. Good luck!
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