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absa_

audiotagging2019

6th place solution to Freesound Audio Tagging 2019 kaggle competition

grokking-the-object-oriented-design-interview

kaggle

loan_prediction

npm-module

S3 wrapper

object-detection-with-deep-learning-and-sliding-window

Introduces an approach for object detection in an image with sliding window. The repository contains three files, make_data.py reads the image in gray scale and converts the image into a numpy array. The labels are also appended based on the file name. In this case, if the file name starts with "trn", then 1 is appended else 0. Finally, all the images and labels are saved into .npy file. The test-model-1.py file loads the images and converts the labels into two categories as we are doing binary classification of images. The model is built using keras with theano as backend. In this case, the best training accuracy was 80% since the data was just 500 images and the testing accuracy was 67%

s3wrapper

app for aws using node

shark

Development in Shark has been ended.

standard

Standard objects format for all CSSinJS implementations.

todo