Digit Recognizer

Python Jupyter Notebook with Convolutional Neural Network digit recognizer implemented in Keras. It's Google Colab ready.

Part of the Kaggle competition.

Submitted Kernel with 0.995 score.

Check out corresponding Medium article:

Digit Recognizer - Introduction to Kaggle Competitions with Image Classification Task (0.995)

Data

Dataset: MNIST Handwritten digits

Description: Classification of handwritten digits, 10 classes (0-9).

Training: 37.8k (0.9) images

Validation: 4.2k (0.1) images

Testing: 28k images

Model

_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
conv2d_22 (Conv2D)           (None, 28, 28, 32)        832       
_________________________________________________________________
conv2d_23 (Conv2D)           (None, 28, 28, 32)        25632     
_________________________________________________________________
max_pooling2d_11 (MaxPooling (None, 14, 14, 32)        0         
_________________________________________________________________
dropout_7 (Dropout)          (None, 14, 14, 32)        0         
_________________________________________________________________
conv2d_24 (Conv2D)           (None, 14, 14, 64)        18496     
_________________________________________________________________
conv2d_25 (Conv2D)           (None, 14, 14, 64)        36928     
_________________________________________________________________
max_pooling2d_12 (MaxPooling (None, 7, 7, 64)          0         
_________________________________________________________________
dropout_8 (Dropout)          (None, 7, 7, 64)          0         
_________________________________________________________________
flatten_4 (Flatten)          (None, 3136)              0         
_________________________________________________________________
dense_8 (Dense)              (None, 8192)              25698304  
_________________________________________________________________
dropout_9 (Dropout)          (None, 8192)              0         
_________________________________________________________________
dense_9 (Dense)              (None, 2048)              16779264  
_________________________________________________________________
dropout_10 (Dropout)         (None, 2048)              0         
_________________________________________________________________
dense_10 (Dense)             (None, 10)                20490     
=================================================================
Total params: 42,579,946
Trainable params: 42,579,946
Non-trainable params: 0
_________________________________________________________________

Training

Results

Kaggle score: 0.995

Author

Greg (Grzegorz) Surma

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