Pinned Repositories
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.
todo
avinanand's Repositories
avinanand/grokking-the-object-oriented-design-interview
avinanand/npm-module
S3 wrapper
avinanand/s3wrapper
app for aws using node
avinanand/todo
avinanand/Absa_
avinanand/audiotagging2019
6th place solution to Freesound Audio Tagging 2019 kaggle competition
avinanand/Kaggle
avinanand/Loan_Prediction
avinanand/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%
avinanand/shark
Development in Shark has been ended.
avinanand/standard
Standard objects format for all CSSinJS implementations.