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*Initiate the idea of data preprocessing: create proper input dataset for the CNN model
'''5/2/2019'''
*Work on data preprocessing
'''5/16/2019'''*Keep working on data preprocessing*Generate screenshot
'''5/7/2019'''*Research some issues occurred during screenshot generating (Will work on how this more tomorrow)*try to feed Mixed data: categorical + images to our set up CNN model**https://www.pyimagesearchdatacamp.com/community/tutorials/cnn-tensorflow-python '''5/8/2019'''*fix the screenshot tool by switching to Firefox*Data preprocessing '''5/0212/042019'''*Finish image data preprocessing '''5/13/keras2019'''*Set up initial CNN model using Keras**issue: Keras freezes on last batch of first epoch, make sure the following: steps_per_epoch = number of train samples//batch_size validation_steps = number of validation samples//batch_size '''5/14/2019'''*Implement the CNN model *Work on some changes in the data preprocessing part (image data)**place class label in image filename '''5/15/2019'''*Correct some out-multiple-inputsof-date data in <code>The File to Rule Them ALL.csv</code>, new file saved as <code>The File to Rule Them ALL_NEW.csv</code>*implement generate_dataset.py and-mixed-sitmap tool**regenerate dataset using updated dataand tool '''5/16/2019'''*Object detection using implementation on CNN*Some problems to consider:**some websites have more than 1 cohort page: a list of cohorts for each year**class label is highly imbalanced: https://gluontowardsdatascience.mxnet.iocom/chapter08_computerdeep-learning-visionunbalanced-training-data-solve-it-like-this-6c528e9efea6  '''5/object-detection.html17/2019'''*have to go back with the old plan of separating image data :(*documentation on wiki*test run on the GPU server
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