Dear readers and contributors,
We hope you enjoy the new articles chosen for this week:
Deep learning gender from name -LSTM Recurrent Neural Networks
By Deepak Babu P R – 4 min read.
Deep learning neural networks have shown promising results in problems related to vision, speech and text with varying degrees of success. I have tried looking at a text problem here, where we are trying to predict gender from name of the person.
The Royal Society report on Machine Learning (April 2017)
By Julian Harris – 10 min read.
The Royal Society launched a (128 page!) report on machine learning. I’ve waded through it and taken some notes from it where there are things usefully different or conveyed in useful ways, that others may find useful. Here and there I’ve linked to other work I’ve found and added a few observations.
Analytics on the New York rental market | Top 15% on Kaggle!
By Shubhankar Srivastava— 9 min read.
This is a documentation of my first serious take on a Kaggle competition – Renthop rental inquiries. Two and a half months, 146 git commits and 87 submissions later, I stand within the Top 15% on the leaderboard – a position I’m proud of!
My experience participating in Kaggle Data Science Bowl 2017 (Lung Cancer Detection)
By Ashish Shah – 4 min read.
I participated in Kaggle’s annual Data Science Bowl (DSB) 2017and would like to share my exciting experience with you. To begin, I would like to highlight my technical approach to this competition.
Data and Mental Health: The OSMI Survey 2016
By The Fluffy Mammal – 16 min read.
Hi everyone! First of all, I want to thank my friends, the CMU community, and Medium for providing thoughtful feedback on my last article. The stories shared and conversation had over the article have been touching, and I am really happy that the article contributed to the discussion on mental health at CMU.