YOLOX: Exceeding YOLO Series in 2021

The paper featuring some improvements that were made to YOLO series, to create a new high-performance detector called YOLOX. It includes the results of testing the detector.
https://bit.ly/3CkEkGm

​​Sourcing top tech talent is always a challenge... Yeap, we've all been there!

Data Phoenix can offer some help. Did you know that you can publish your job opportunities in our digest for free? If you have open positions in Data Science, Machine Learning, Data Engineering, MLOps, etc., don't hesitate to contact us!

Contact email: editor@dataphoenix.info

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

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

​​Hi friends! The Data Phoenix team invites you all August 17 to the first of our series of MLOps webinars ennoscriptd "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

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

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

💡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

​​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.

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

📌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

​​Good morning people! It's Sunday and the best way to start your day is to smile!🤗

💡SynLiDAR: Learning From Synthetic LiDAR Sequential Point Cloud for Semantic Segmentation

SynLiDAR is a synthetic LiDAR point cloud dataset that contains large-scale point-wise annotated point cloud with accurate geometric shapes and comprehensive semantic classes, which the authors used to design PCT-Net, to narrow down the gap with real-world point cloud data.
https://bit.ly/3CvT5WC

📚Designing, Visualizing and Understanding Deep Neural Networks

A collection of lectures on Deep Learning delivered by Sergey Levine at UC Berkeley in 2020/21. In total, the course features 66 lectures, from the ML basics to policy gradients and meta learning.
https://bit.ly/3fKyEMd

📌Alias-Free Generative Adversarial Networks

The synthesis process of typical generative adversarial networks depends on absolute pixel coordinates in an unhealthy manner. The authors trace its root cause and derive architectural changes that guarantee that unwanted information cannot leak into hierarchical synthesis.
https://bit.ly/3ix7E4v

Tired of a huge amount of information coming up every day and want to read only the best?

Subscribes to our channels to get hand-picked articles, papers, and tutorials that will help you to achieve higher results in your career

@ml_world - All about Machine Learning and Data Science

@devs_world - All about Software Development, DevOps, System Design, Career building

📌OpenAI releases OpenAI Codex, an advanced AI system that translates natural language to code. The release is available through their API in private beta.
https://bit.ly/3fVTc4f
https://bit.ly/3fVTc4f)

💡C. Light Technologies is to design and build the AI solution that spots changes in eye motion to detect the earliest stage of Alzheimer’s disease.
https://bit.ly/2VNHySe

Hey friends!👋🏻
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/3AwkJkw

📌Building Architectures that Can Handle the World’s Data

Perceiver is a general-purpose architecture that can process data including images, point clouds, audio, video, and their combinations. Learn more about this universal architecture!

https://bit.ly/2VLxCc2