Assignment 3 of Machine Learning Course: miniature of ImageNet classification challenge.

Achieved Accuracy of 83.30%, placed to 2nd rank.

Using Xception Model, loading pre-trained Imagenet weights and fine-tuning to achieve better validation accuracy.

10% of the data used for validation, rounding up to 90,000 train images, and 10,000 validation images.

Re-structured dataset to the following stucture:

data/ 

   train/
      class1/
      class2/
      
   validation/
      class1/
      class2/

Install dependencies before running the program

pip3 install -r requirements.txt (Python 3.5.2)