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Weekly Selection – Dec 15, 2017

Grow Your Own Experts


by Lucian Lita – 5 min read

If you find yourself in this predicament, consider this: your hiring criteria may be off and your candidate pool may be too narrow.


Youtube Views Predictor

by Aravind Srinivasan – 10 min read

Over the past 5 years YouTube has paid out more than $5 billion to YouTube content creators. Popular YouTuber PewDiePie made $5 million in 2016 from YouTube alone, not including sponsorships, endorsements and other deals outside of YouTube.


VideoFi – Annotating videos and finding insights simplified

by Shivangi Shroff – 5 min read

Watching a video is fun, but trying to analyze the video manually, not so much! You may miss important details and it is quite time consuming. What if the process can be automated? It surely can make life easier for few people.


How to Tell Stories and Weave a Cohesive Narrative With Data

by Payman Taei – 5 min read

Storytelling is one of the most important evolutionary advantages humans have. That is a bold statement, but I believe it is true.


Working with Missing Data in Machine Learning

by Boyan Angelov – 4 min read

Missing values are representative of the messiness of real world data. There can be a multitude of reasons why they occur – ranging from human errors during data entry, incorrect sensor readings, to software bugs in the data processing pipeline.


MangaGAN

by Béthy – 8 min read

Manga and anime are appreciated around the world for their intricate art styles and compelling stories. The fan base for this is so massive there are thousands of artists out there drawing original manga and anime characters, and also thousands who are tempted to create them.


Using Object detection for a Smarter Retail Checkout Experience

by Priya Dwivedi – 4 min read

I have been playing around with the Tensorflow Object Detection API and have been amazed by how powerful these models are. I want to share the performance of the API for some practical use cases.


Machine Translation to Shakespearian English

by Ludi Rehak – 4 min read

If you’ve been following the latest developments in deep learning, you’ve probably come across artistic style transfer. It’s a technique to create a new image with the content of image A, in the style of image B.


A very simple demo of interactive controls on Jupyter notebook

by Tirthajyoti Sarkar – 5 min read

Project Jupyter/IPython has left one of the biggest degrees of impact on how a data scientist can quickly test and prototype his/her idea and showcase the work to peers and open-source community. It is a non-profit, open-source project, born out of the IPython Project in 2014, which rapidly evolved to support interactive data science and scientific computing across all major programming languages.


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