On 6 of October in Kiev will take place an interesting Computer Vision Conference https://www.facebook.com/events/1690893937643933/

- 6 speakers:
- Pedro Porto Buarque de Gusmão - Postdoctoral Researcher, Department of Computer Science, University of Oxford, United Kingdom
- Eugene Khvedchenia - Computer Vision Consultant, CloudCV
- Bohdan Zhurakovskyi - Machine Learning Engineer at BetConstruct
- Sergiy Koshel- Lead Data Scientist at Infopulse
- Kyryl Truskovskyi - Lead Researcher, Neuromation
- Raid Arfua - Machine Learning Engineer at BetConstruct

- Lunch included. Afterparty with beer and good people is waiting for you!

- 2 workshops - For the workshops you only need to bring your laptop. Computational resources will be provided.

Also you can save 20% with using promo code: AndreyNikishaevFriends
Tickets: https://www.aibooster.com.ua/cv2018/

See you there )

Python -> Tensorflow transformer https://www.tensorflow.org/guide/autograph

Cool library that will do diferentiation for u)
https://github.com/google/tangent

Good tutorial on AutoGraph from TFDevSummit 2018 https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/contrib/autograph/examples/notebooks/dev_summit_2018_demo.ipynb

Awesome network to synchronize video and music beats - dancification
https://youtu.be/K3z68mOLbNo

New interesting information about parasites which makes ant-zombies was discovered with help of deep networks
http://www.pnas.org/content/early/2017/11/06/1711673114.full

Why pipelines with small and simple algorithms almost always better then DNN
https://blogs.dropbox.com/tech/2016/08/fast-and-accurate-document-detection-for-scanning/

Short guide to ML for non ML engineers (russian)
https://vas3k.ru/blog/machine_learning/

GANs used to augment MRI images https://youtu.be/BMuFk2PjEuM

Interesting work on representation learning
http://www3.cs.stonybrook.edu/~cvl/dae.html

Beautiful math visual experiment
https://johnhw.github.io/umap_primes/index.md.html

Coming out for those who likes math and NN, but was afraid of community response))
Kiev(200UAH)
https://m.facebook.com/story.php?story_fbid=1891768030907526&id=100002230412876

Nice publication about ML stuff)
https://thegradient.pub/

New awesome Dataset for Aerial Object Detection https://captain-whu.github.io/DOTA/

Fresh Style Transfer Network paper https://www.youtube.com/watch?v=dyzn3Fmtw-E

Its seem that this week is wee of art)) new cool paper with code!! on Distill.
Now you be able to create awesome parametrized art)
https://distill.pub/2018/differentiable-parameterizations/

"Large Scale GAN Training for High Fidelity Natural Image Synthesis
"
New best imagenet conditional GAN with impressive results and 100 points better FID
https://arxiv.org/abs/1809.11096

Interesting Podcast about ML https://itunes.apple.com/us/podcast/this-week-in-machine-learning/id1116303051?mt=2