Those who want to understand #GAN s better can now play with them in the browser with GAN lab.

https://towardsdatascience.com/gan-lab-train-gans-in-the-browser-21a423585460

#Google introduced Conceptual Captions, a new dataset and challenge for image captioning consisting of ~3.3 million image/caption pairs for the machine learning community to train and evaluate their own image captioning models.

Link: https://ai.googleblog.com/2018/09/conceptual-captions-new-dataset-and.html

#dataset

Upcoming spolitght at #NIPS2018 «Realistic Evaluation of Deep Semi-Supervised Learning Algorithms»

Link: https://arxiv.org/abs/1804.09170

OpenAI’s Long Pursuit of Dota 2 Mastery

Full story of the project on medium

https://medium.com/syncedreview/openais-long-pursuit-of-dota-2-mastery-1d3a861472bd

#OpenAI

#netflixresearch has published a YouTube playlist to make people learn about how they improve various aspects of Netflix including personalized algorithms, content valuation, and streaming optimization:

https://www.youtube.com/playlist?list=PL_S_WRR3d9p2J5IILdSS2OGCF8s3E0kjQ

And #Google also launched #DataSet search. This is a huge breakthrough for the DS community, because now it will be easier to access some interesting data.

https://toolbox.google.com/datasetsearch

Predicting Popularity of The New York Times Comments (Part 1)


Article with the #NLP research of NYT comments. Nice example of the applied #research job.

Link: https://towardsdatascience.com/predicting-popularity-of-the-new-york-times-comments-part-1-d32f26261f6f
Github: https://github.com/sakshi716/nyt-nlp-capstone

How to Create Animated Graphs in Python

Short tutorial on how to create animated graphs, which also works in #jupyter notebooks.

Link: https://towardsdatascience.com/how-to-create-animated-graphs-in-python-bb619cc2dec1
Youtube link with #visualization: https://youtu.be/7xrvuSDLHiY|

#novice #beginner

Predicting Popularity of The New York Times Comments (Part 1)


Article with the #NLP research of NYT comments. Nice example of the applied #research job.

Link: https://towardsdatascience.com/predicting-popularity-of-the-new-york-times-comments-part-1-d32f26261f6f
Github: https://github.com/sakshi716/nyt-nlp-capstone

Healthcare Dataset with #PySpark

Back to some #BigData stuff: article about quick-and-dirty development of prediction algorithm using #Spark engine.

Link: https://towardsdatascience.com/healthcare-dataset-with-spark-6bf48019892b

Multimodal Unsupervised Image-to-Image Translation (MUNIT)

Arxiv: https://arxiv.org/abs/1804.04732
Github: https://github.com/NVlabs/MUNIT

Note how posture and scene proportions are retained after transition.

There is a chart for CS research citation rate: https://www.iro.umontreal.ca/~bengioy/citation-rate-CS-1sept2018.html

Looks like the #dl is eating the world of software atm.

#academy #chart

Useful tool for #crowdsourcing annotation and labeling: https://prodi.gy

Something on #SoftwareDevelopment

Data Types From A Machine Learning Perspective With Examples

This is a really #beginner level article about how different data types can be categorized.

Link: https://towardsdatascience.com/scala-for-data-science-engineering-part-1-6a0a5738d7b0

After election scandal, #facebook surges to fight fake news, and that’s how is it going now.

https://techcrunch.com/2018/09/13/photo-video-fact-checking/

#nlp #ai #fakenews

NVIDIA's article on #AI training and validation infrastructure for autonomous driving with MagLev, introduced at #facebook event.

https://blogs.nvidia.com/blog/2018/09/13/how-maglev-speeds-autonomous-vehicles-to-superhuman-levels-of-safety/

#selfdriving #ci

How Booking.com increases the power of online A/B experiments with CUPED

Link: https://booking.ai/how-booking-com-increases-the-power-of-online-experiments-with-cuped-995d186fff1d

#ab #statistics #booking

#OpenDataScience community (ods.ai) recently released Open Machine Learning Course. This is a community-driven course, covering #production, #Kaggle (actually #CompetitiveDataScience, but we use this hashtag for the first time), #DL, #RL, #ML and validated on the russian-speaking DS community, which was translated into english.

There are lots of assignments and some competitions during the course. Interactive rating highly motivates and makes it fun to participate.

Next session starts on October 1. Welcome!

Link: https://mlcourse.ai?utm_source=telegram&utm_medium=opendatascience