Great Github and Reddit resources for machine learning

Here are links to 5 Github repositories and 2 Reddit discussions devoted to Machine learning. Actually, this is mostly copy of the original post on Analitcs Vidhya: 5 Amazing Machine Learning GitHub Repositories & Reddit Threads from September 2018.

Gihub repos

1. Papers with code


List of research articles (links to original PDFs are given). Each article is accompanied by sorce code of the software, so it should be not hard to understand the implementation of the algorithms. New links are added weekly.

2. Deep learning object detection


A list of top object detection algorithms since 2014. Implementation code is available for multiple frameworks: tensorflow, keras, caffe, pytorch.

3. Reproduce ImageNet in 18 minutes


Code to reproduce ImageNet in 18 minutes.

4. Concurrent data pipelines made easy


Pypeline is a simple yet very effective Python library for creating concurrent data pipelines. The aim of this library is to solve low to medium data tasks (that involve concurrency or parallelism) where the use of Spark might feel unnecessary.

5. Everybody Dance Now – Pose Estimation


This repo presents a simple method for “do as I do” motion transfer: given a source video of a person dancing we can transfer that performance to a novel (amateur) target after only a few minutes of the target subject performing standard moves. We pose this problem as a per-frame image-to-image translation with spatio-temporal smoothing. Using pose detections as an intermediate representation between source and target, we learn a mapping from pose images to a target subject’s appearance.

Reddit discussions

1. Beginner friendly AI papers to implement


Easy-for-beginner research papers for implementation.

2. Overcoming troubles reading a particular paper


This thread has all the answers how community deals with problems in reading research papers.