mlwhiz

13 ms·

61.
Learning Spark Using Python: Basics and Applications(mlwhiz.com)
1 points by mlwhiz 8y ago|0 comments
62.
Top Free Data Science Resources on the Internet(mlwhiz.com)
3 points by mlwhiz 8y ago|0 comments
63.
by mlwhiz 8y ago
Yes. They provide this in the R-CNN paper, "Compared to the multi-feature, non-linear kernel SVM approach, we achieve a large improvement in mAP, from 35.1% to 53.7% mAP, while also being much faster". Also in the metrics provided
64.
How to Win a Data Science Competition(mlwhiz.com)
2 points by mlwhiz 8y ago|0 comments
65.
by mlwhiz 8y ago
A look at different papers on Object Detection. Mainly Covering RCNN to Faster RCNN Journey. ANd the intuition behind
66.
How to Move from Keras to Pytorch – Answer(mlwhiz.com)
4 points by mlwhiz 8y ago|0 comments
67.
Top Data Science Resources on the Internet Right Now(mlwhiz.com)
3 points by mlwhiz 8y ago|0 comments
68.
Object Detection: An End-to-End Theoretical Perspective(mlwhiz.com)
62 points by mlwhiz 8y ago|5 comments
69.
Text Preprocessing Methods for Deep Learning(mlwhiz.com)
50 points by mlwhiz 8y ago|0 comments
70.
The best way to leave keras and move to pytorch(mlwhiz.com)
2 points by mlwhiz 8y ago|0 comments
71.
My Tryst with MCMC Algorithms(mlwhiz.com)
3 points by mlwhiz 8y ago|0 comments
72.
Behold the power of MCMC(mlwhiz.com)
3 points by mlwhiz 8y ago|1 comments
73.
Create Graphs with SeaBorn- the Most Awesome Python Library for Visualization(mlwhiz.com)
4 points by mlwhiz 8y ago|0 comments
74.
A Layman's Guide to Moving from Keras to Pytorch(mlwhiz.com)
2 points by mlwhiz 8y ago|0 comments
75.
Object Detection: An End to End Journey(mlwhiz.com)
2 points by mlwhiz 8y ago|0 comments
76.
A Layman Guide to Moving from Keras to Pytorch(mlwhiz.com)
4 points by mlwhiz 8y ago|0 comments
77.
Connected Components – The one Graph Algorithm you need to know(mlwhiz.com)
113 points by mlwhiz 8y ago|12 comments