Meet the BIG AWS Dev Day Kyiv 2019!
What is it, #AWSDevDayKyiv?
It's a free, full-day technical event where new developers will learn about some of the hottest topics in cloud computing, and experienced developers can dive deep on AWS services.
The conference brings together the Ukrainian cloud computing community to connect, collaborate, and learn about AWS.
What makes AWS Dev Day so special?
• 10 strong technical specialists to share their experience
• 3 tracks with subject matters and specific themes
• Ask an AWS Architect, where you can get a 1:1 session with a member of the AWS Solutions Architect Team.
In this action-packed one-day event you can choose to attend 3 tracks:
☁ Modern App Development
☁ Machine Learning
☁ Backends & Architecture
Hot topics on the ML track: «Add intelligence to applications with AWS ML Services», «Build models for Amazon SageMaker», «Scaling ML from 0 to millions of users», «Building a Modern Data platform in the Cloud».
When?
Tuesday, June 11 | 9AM - 5PM
Where?
"Mercure", Vadyma Hetmana Street 6, Kyiv
Participation is free of charge. Please, fill in the registration form below.
👉 Register now: https://provectus.com/events/#event-11-June-2019-aws-dev-day-kyiv
Learn more: https://awsdevday.kyiv.provectus.com
What is it, #AWSDevDayKyiv?
It's a free, full-day technical event where new developers will learn about some of the hottest topics in cloud computing, and experienced developers can dive deep on AWS services.
The conference brings together the Ukrainian cloud computing community to connect, collaborate, and learn about AWS.
What makes AWS Dev Day so special?
• 10 strong technical specialists to share their experience
• 3 tracks with subject matters and specific themes
• Ask an AWS Architect, where you can get a 1:1 session with a member of the AWS Solutions Architect Team.
In this action-packed one-day event you can choose to attend 3 tracks:
☁ Modern App Development
☁ Machine Learning
☁ Backends & Architecture
Hot topics on the ML track: «Add intelligence to applications with AWS ML Services», «Build models for Amazon SageMaker», «Scaling ML from 0 to millions of users», «Building a Modern Data platform in the Cloud».
When?
Tuesday, June 11 | 9AM - 5PM
Where?
"Mercure", Vadyma Hetmana Street 6, Kyiv
Participation is free of charge. Please, fill in the registration form below.
👉 Register now: https://provectus.com/events/#event-11-June-2019-aws-dev-day-kyiv
Learn more: https://awsdevday.kyiv.provectus.com
Рrovectus
Events Archives
Learn about some of the Provectus past events in the archive. Kindly explore the Insights tab for more educational, useful content!
#junior
Good introduction article about base things
https://towardsdatascience.com/estimators-loss-functions-optimizers-core-of-ml-algorithms-d603f6b0161a
Good introduction article about base things
https://towardsdatascience.com/estimators-loss-functions-optimizers-core-of-ml-algorithms-d603f6b0161a
Medium
Estimators, Loss Functions, Optimizers —Core of ML Algorithms
In order to understand how a machine learning algorithm learns from data to predict an outcome, it is essential to understand the…
From today our channel also be presented on FB and Twitter
FB: https://www.facebook.com/mlworld
Twitter: https://twitter.com/mlwcommunity
FB: https://www.facebook.com/mlworld
Twitter: https://twitter.com/mlwcommunity
Facebook
Log in or sign up to view
See posts, photos and more on Facebook.
Great article on image enhancing (without NN!!!!)
https://sites.google.com/view/handheld-super-res/
https://sites.google.com/view/handheld-super-res/
Google
Handheld Multi-Frame Super-Resolution
We present a multi-frame super-resolution algorithm that supplants the need for demosaicing in a camera pipeline by merging a burst of raw images. In the above figure we show a comparison to a method that merges frames containing the same-color channels…
Good overview article for 3D pose estimation
https://blog.nanonets.com/human-pose-estimation-3d-guide/
https://blog.nanonets.com/human-pose-estimation-3d-guide/
Nanonets
Intelligent document processing with AI | Nanonets
AI-based intelligent document processing with Nanonets' self-learning OCR. Automate data capture from invoices, receipts, passports, ID cards & more!
Model optimization with new Tensorflow tool
https://medium.com/tensorflow/tensorflow-model-optimization-toolkit-pruning-api-42cac9157a6a
https://medium.com/tensorflow/tensorflow-model-optimization-toolkit-pruning-api-42cac9157a6a
Medium
TensorFlow Model Optimization Toolkit — Pruning API
Since we introduced the Model Optimization Toolkit — a suite of techniques that developers, both novice and advanced, can use to optimize…
Google creating next level translation app, Star Trek translator is not so far as we though)
https://www.technologyreview.com/s/613559/google-ai-language-translation/
https://www.technologyreview.com/s/613559/google-ai-language-translation/
MIT Technology Review
Google’s AI can now translate your speech while keeping your voice
Researchers trained a neural network to map audio “voiceprints” from one language to another.
Unsupervised Learning with Graph Neural Networks
Videos from workshop http://www.ipam.ucla.edu/programs/workshops/workshop-iv-deep-geometric-learning-of-big-data-and-applications/?tab=schedule
Slides: http://helper.ipam.ucla.edu/publications/glws4/glws4_15546.pdf
Videos from workshop http://www.ipam.ucla.edu/programs/workshops/workshop-iv-deep-geometric-learning-of-big-data-and-applications/?tab=schedule
Slides: http://helper.ipam.ucla.edu/publications/glws4/glws4_15546.pdf
IPAM
Workshop IV: Deep Geometric Learning of Big Data and Applications - IPAM
Pytorch implementation of Augmented Neural ODEs
https://arxiv.org/abs/1904.01681
https://github.com/EmilienDupont/augmented-neural-odes
https://arxiv.org/abs/1904.01681
https://github.com/EmilienDupont/augmented-neural-odes
Interesting new model, faster and smaller the all before
https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet
https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet
GitHub
tpu/models/official/efficientnet at master · tensorflow/tpu
Reference models and tools for Cloud TPUs. Contribute to tensorflow/tpu development by creating an account on GitHub.
Very interesting paper from Google Research. Generating video from first and end frames
https://arxiv.org/pdf/1905.10240.pdf
https://arxiv.org/pdf/1905.10240.pdf
From Ian Goodfellow https://twitter.com/goodfellow_ian/status/1133528189651677184
"1/7 Do word embeddings really say that man is to doctor as woman is to nurse? Apparently not. Check out this thread for a description of a short paper I co-wrote with Malvina Nissim and Rob van der Goot, available here: (link: https://arxiv.org/abs/1905.09866) arxiv.org/abs/1905.09866 #NLProc #bias"
"1/7 Do word embeddings really say that man is to doctor as woman is to nurse? Apparently not. Check out this thread for a description of a short paper I co-wrote with Malvina Nissim and Rob van der Goot, available here: (link: https://arxiv.org/abs/1905.09866) arxiv.org/abs/1905.09866 #NLProc #bias"
#vacancy #job #python
Big video analytic company are looking for Data Engineer and Infrastructure Engineer.
Data: 10+Pb + 10Tb/day
Sallary: $4k-6k + shares after 1 year
Office: Kyiv, Gulliver
Description: http://bit.ly/2HOeEaW
Contact: https://www.facebook.com/taras.shumyk
Big video analytic company are looking for Data Engineer and Infrastructure Engineer.
Data: 10+Pb + 10Tb/day
Sallary: $4k-6k + shares after 1 year
Office: Kyiv, Gulliver
Description: http://bit.ly/2HOeEaW
Contact: https://www.facebook.com/taras.shumyk
Google Docs
Data Engineer Position
"Gauge Equivariant Convolutional Networks and the Icosahedral CNN
" pretty interesting way of thinking, i like that
https://arxiv.org/pdf/1902.04615.pdf
" pretty interesting way of thinking, i like that
https://arxiv.org/pdf/1902.04615.pdf
Collection of pretrained models for PyTorch
https://github.com/rwightman/pytorch-image-models
https://github.com/rwightman/pytorch-image-models
GitHub
GitHub - huggingface/pytorch-image-models: The largest collection of PyTorch image encoders / backbones. Including train, eval…
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V...
Notes from Karpathy on common mistakes when training NN
http://karpathy.github.io/2019/04/25/recipe/
http://karpathy.github.io/2019/04/25/recipe/
karpathy.github.io
A Recipe for Training Neural Networks
Musings of a Computer Scientist.
Learning Perceptually-Aligned Representations via Adversarial Robustness
https://arxiv.org/abs/1906.00945
Github: https://github.com/MadryLab/robust_representations
https://arxiv.org/abs/1906.00945
Github: https://github.com/MadryLab/robust_representations
New interesting paper to read, on face generation(faster then GANs)
https://arxiv.org/abs/1906.00446
https://arxiv.org/abs/1906.00446
arXiv.org
Generating Diverse High-Fidelity Images with VQ-VAE-2
We explore the use of Vector Quantized Variational AutoEncoder (VQ-VAE) models for large scale image generation. To this end, we scale and enhance the autoregressive priors used in VQ-VAE to...
In case that you didn't read that awesome research about wellness. So if you asked yourself why, that's real answer
https://arxiv.org/abs/1802.07068
https://arxiv.org/abs/1802.07068
arXiv.org
Talent vs Luck: the role of randomness in success and failure
The largely dominant meritocratic paradigm of highly competitive Western cultures is rooted on the belief that success is due mainly, if not exclusively, to personal qualities such as talent,...