Stanford engineers have combined two types of computers to create a faster and less energy-intensive image processor for use in autonomous vehicles, security cameras and medical devices.

https://news.stanford.edu/2018/08/17/new-ai-camera-revolutionize-autonomous-vehicles/

Recent Advances for a Better Understanding of Deep Learning − Part I

https://towardsdatascience.com/recent-advances-for-a-better-understanding-of-deep-learning-part-i-5ce34d1cc914

#dl #theory

What is a Generative Adversarial Network?

Another article about how GANs work.

https://hunterheidenreich.com/blog/what-is-a-gan/

#gan #theory #dl

Curious About How To Be A Data Scientist? Hear From A Netflix Data Scientist

Article about how data science #production works. How problem should be defined and how project should be maintained and run.

https://towardsdatascience.com/a-peek-into-a-netflix-data-scientists-day-66bf3dacabb9

First 1e6 integers, represented as binary vectors indicating their prime factors, and laid out using the sparse matrix support in leland_mcinnes's UMAP dimensionality reduction algorithm. This is from a 1000000x78628 (!) binary matrix. Very pretty structure emerges.

"Learning Hierarchical Semantic Image Manipulation through Structured Representations":

https://arxiv.org/abs/1808.07535

#cv #dl

Online ad demand prediction #kaggle competition 1st place summary:
https://www.kaggle.com/c/avito-demand-prediction/discussion/59880

Winner explains how to combine categorical, numerical, image and text features into a single #NN that gets you into top 10 without stacking.

#PyTorch tensor basics: https://www.kdnuggets.com/2018/05/pytorch-tensor-basics.html

New model to naturally detect depression in conversations

Link: https://news.mit.edu/2018/neural-network-model-detect-depression-conversations-0830

#nlp #audio #dl

Tickets for one of the key conferences #NIPS2018 were sold out in 15 minutes.

NIPS Conference Registrations 2002 thru 2019.
[2018] War erupts for tickets
[2019] AI researchers discover time travel.

#NIPS2018

1st place solution in the recent Home Credit Default Risk #Kaggle competition

- extensive feature engineering, with ~700 of features total used
- XGBoost, LightGBM, CatBoost, FastRGF, DAE+NN, Lin Reg
- 3-level ensembling (stacking x2 + blending)

Link: https://www.kaggle.com/c/home-credit-default-risk/discussion/64821

More on that model in the Wired article: https://thenextweb.com/artificial-intelligence/2018/09/05/mits-depression-detecting-ai-might-be-its-scariest-creation-yet/

The article notes that the best advantage of suggesting approach is that it is context-free.

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