Data Phoenix

2021-08-07 10:00:04 Image Super-Resolution via Iterative Refinement

Chitwan Saharia et al. present SR3, an approach to image Super-Resolution via Repeated Refinement. SR3 adapts denoising diffusion probabilistic models to conditional image generation and performs super-resolution through a stochastic denoising process.
https://bit.ly/3AiBdN3 Open / Comment

2021-08-06 15:00:31 We know that some of you are looking for job opportunities now. We've put together a list of 10 amazing positions available this week. Stay tuned!

1) Computer Vision Engineer, SoftServe
https://bit.ly/3AgsJWL
2) Data Scientist (Advanced Analytics), SoftServe
https://bit.ly/2TWkijW
3) Data Engineer, Fintech Solutions, DataArt
https://bit.ly/3itAcvE
4) Senior IT Data Analyst, Raiffeisen Bank
https://bit.ly/3rVsjSO
5) R&D CV/ML Engineer, Augmented Pixels
https://bit.ly/3AkaVtM

For other 5 positions click https://bit.ly/3Aklzkf Open / Comment

2021-08-06 15:00:28 ​​Hey folks!

As you might already know, Data Phoenix is now offering you all a unique opportunity to host and promote your content at our website and in the digest itself. We're looking for original submissions and contributions, but we also consider reposts.

So, if you have any content that's truly awesome and that's worth sharing with the community, kindly reach out to us at editor@dataphoenix.info to discuss how it's going to work. Open / Comment

2021-08-06 10:00:05 Elastic Graph Neural Networks

In this paper, the authors introduce a family of GNNs (Elastic GNNs) based on ℓ1 and ℓ2-based graph smoothing and propose a novel and general message passing scheme into GNNs. Experiments demonstrate that Elastic GNNs obtain better adaptivity on benchmark datasets.
https://bit.ly/3lBHYWj Open / Comment

2021-08-05 15:00:07 The latest issue of the digest is already waiting for you on our website! New articles, papers, books, and more! Tap on the link and feel free to subscribe
https://bit.ly/3Cd0sSZ
https://bit.ly/36UjEGI Open / Comment

2021-08-05 13:40:10 Data Phoenix pinned «​​Hi friends! The Data Phoenix team invites you all August 17 to the first of our series of MLOps webinars entitled "The A-Z of Data" During the pilot webinar — "The A-Z of Data: Introduction to MLOps" — we will explore what MLOps is, MLOps principles and…» Open / Comment

2021-08-05 10:00:05 Natural Language Processing [Huggingface Course]
During this course, you'll learn the basics of NLP using libraries from the Hugging Face ecosystem — Transformers, Datasets, Tokenizers, and Accelerate — as well as the Hugging Face Hub.
https://bit.ly/3CsFcZA Open / Comment

2021-08-04 18:46:54 ​​Hi friends! The Data Phoenix team invites you all August 17 to the first of our series of MLOps webinars entitled "The A-Z of Data" During the pilot webinar — "The A-Z of Data: Introduction to MLOps" — we will explore what MLOps is, MLOps principles and best practices, major tools for MLOps implementation, and several architecture implementations. We will start with a basic ML lifecycle and move forward to best practices of building complicated, fully automated MLOps pipelines.

Speaker

Dmitry Spodarets — Head of R&D at VITech; active participant of the Open Data Science community; AWS Competency in Machine Learning.

"The A-Z of Data"— A series of webinars from Data Phoenix Events designed to help data scientists, data engineers, and all interested in data to expand the horizons of their AI/data expertise.

Stay tuned! It will be fun!
https://bit.ly/3jqh8NY Open / Comment

2021-08-04 15:00:08 Are you on board and receive our weekly newsletter? Not yet? Well, no need to wait! Fill in your email and get instant access to all the AI/ML goodies in one go. Looking forward to having you as one of our amazing subscribers!
https://bit.ly/3wHOPPM Open / Comment

2021-08-04 10:00:08 You Do Not Need a Bigger Boat: Recommendations at Reasonable Scale in a (Mostly) Serverless and Open Stack

The authors argue that immature data pipelines are preventing practitioners from leveraging the latest research on recommender systems. Check out what they propose with Serverless.
https://bit.ly/2Vx9cSP Open / Comment