📚DocTr: Document Image Transformer for Geometric Unwarping and Illumination Correction

Hao Feng et al. propose a new framework, called Document Image Transformer (DocTr), to address the issue of geometry and illumination distortion of the document images.

https://bit.ly/3mIR9V4

Hello everyone! Data Phoenix team is ready to present our weekly issue of the digest! And it is already waiting for you on our website! Tap on the link and feel free to subscribe 👇🏻
https://bit.ly/3COMbvA

📌Linux Foundation to promote dataset sharing and software dev techniques

The Linux Foundation announces Project OpenBytes and the NextArch Foundation. OpenBytes is an “open data community” and a new data standard and format for AI apps, while NextArch will build software development architectures that support a range of environments.

https://bit.ly/3nWuHHq

​​⚡️Hello friends! How is your weekend going?
Data Phoenix prepared for you the list of free vacancies for the week. Kindly check it out and let us know what you think 😉

1) Director of Data Operations - GitHub, Remote (US / Canada)
https://bit.ly/3qbO2ah
2) Engineering Manager, Machine Learning - Grammarly, Kyiv, Remote
https://bit.ly/3BKOyOE
3) Sr. Field Data Scientist - Domino Data Lab, Remote
https://bit.ly/3wkVm4z
4) Senior Data Scientist - Intercom, Remote (UK / Ireland)
https://bit.ly/3kdl45Z
5) Data Science Intern (Summer 2022) - Reddit, Remote (US)
https://bit.ly/3bMygdz

Looking to feature your open positions in the digest? Kindly reach out to us at editor@dataphoenix.info for details. We'll be proud to help your business thrive!

​​Good morning friends!
Here's your dose of positivity for this Sunday!🤗
https://bit.ly/3H0Fnh1

💡PyTorch: Transfer Learning and Image Classification

In this tutorial, Adrian Rosebrock will explain how you can perform transfer learning for image classification using the PyTorch deep learning library. Check out part 1 of the tutorial.

https://bit.ly/3BSfLz1

​​⚡️Hello everybody! Today's the day we're going to talk about Dion Hinchcliffe. He's an internationally recognized business strategist, enterprise architect, transformation consultant, futurist, analyst, and in-demand keynote speaker.

Dion's currently a VP and Principal Analyst at Constellation Research where he heads up research and global client advisory into CIO issues, the Future of Work, and emerging enterprise technology. Dion's an industry expert in such areas as enterprise IT, digital transformation, digital workplace, social collaboration, customer experience, API strategy, Enterprise 2.0, Web 2.0, social business, SOA, cloud computing, agile/DevOps, digital business, and IT strategy. His thought leadership can be found on ZDNet, Constellation Research, InformationWeek, ebizQ, On Digital Strategy, and the Enterprise Irregulars. He's also co-authored Web 2.0 Architectures for O’Reilly and the bestselling Social Business by Design (John Wiley & Sons).
https://bit.ly/3H0iFFH

📚Wav2CLIP: Learning Robust Audio Representations From CLIP

Wav2CLIP is a robust audio representation learning method by distilling from CLIP. It can outperform publicly available pre-trained audio representation algorithms.

https://bit.ly/3kjbP4l

📌Neural Radiance Field (NeRF) Papers at ICCV 2021

In anticipation of ICCV (Intl. Conf. on Computer Vision), the author rounded up all papers that use Neural Radiance Fields (NeRFs) that will be represented in the main ICCV2021 conference.

https://bit.ly/3wr3Rep

📚Natural Language Processing (NLP) course

During this course, the students can gain a comprehensive understanding of NLP, from the principles and theories of NLP to various NLP technologies. 12 lectures in total.

https://bit.ly/3mZofA4

💡A Gentle Introduction to Vector Space Models

In this tutorial, you'll learn about vector space, the properties of cosine similarity and how it can help you compare two vectors, and how cosine similarity and L2 distance are different.

https://bit.ly/3qsomX5

⚡️Hello friends, we hope that your day is going great! Data Phoenix team wants to remind you about our weekly newsletter which is coming tomorrow! 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/31HnjrQ

📚Non-deep Networks

In this paper, Ankit Goyal et al. theorize and show that it is possible to build high-performing "non-deep" neural networks by using parallel subnetworks instead of stacking one layer after another.

https://bit.ly/3CdvGbg

⚡️Hi friends!
Data Phoenix team is ready to present our weekly issue of the digest! And it is already waiting for you on our website! Tap on the link and feel free to subscribe 👇🏻
https://bit.ly/3ngpnQd

​​⚡️Hello friends! We hope that your weekend is going great!
Data Phoenix prepared for you the list of free vacancies for the week. Kindly check it out and let us know what you think 😉

1) Product Manager, Machine Learning - Grammarly, Kyiv, Remote
https://bit.ly/3osDO2G
2) Director of Data Operations - GitHub, Remote - US / Canada
https://bit.ly/3qxohBq
3) Machine Learning Engineer - Lyft, Kyiv
https://bit.ly/3HlSPfi
4) Data Scientist - Snap, Kyiv, Odesa, Remote
https://bit.ly/3wF8ulb
5) Research Scientist in HPC and AI Performance - Lawrence Berkeley National Lab, Bay Area, California, United States

Looking to feature your open positions in the digest? Kindly reach out to us at editor@dataphoenix.info

📌 MLOps and DevOps: Why Data Makes It Different

In this article, the O'Reilly team digs into the fundamentals of machine learning as an engineering discipline to answer key questions about MLOps, DevOps, and their evolution through data.

https://bit.ly/31ZNA51

​​We hope your Sunday is going great and you are ready for the upcoming week!
But first things first, here's your weekly dose of positivity🤗
https://bit.ly/3ccpLbO

📚SSAST: Self-Supervised Audio Spectrogram Transformer

In this paper, the authors aim to alleviate the data requirement issues with the AST by leveraging self-supervised learning using unlabeled data for audio and speech classification.

https://bit.ly/3qCwlky

​​⚡️Happy Monday, friends! Today we want to feature Hilary Mason, the Founder of Fast Forward Labs, a machine intelligence research company, and the Data Scientist in residence at Accel.

Previously, she was Chief Scientist at Bitly, co-founded of HackNY, and co-hosted DataGotham. She is a member of NYCResistor. As a Data Scientist in residence at Accel, she provides consulting services to companies large and small about their data strategy.

Hilary spent four years as Chief Scientist at Bitly, where she led the team that studied attention on the internet in real time, doing a mix of research, exploration, and engineering. Also, she co-founded HackNY, a non-profit that helps talented engineering students find their way into the startup community of creative technologists in New York City.

Hilton was a member of Mayor Bloomberg’s Technology and Innovation Advisory Council, which was a great way for her to learn how government and industry can work together.

Did you know about Hilary before? Let us know what you think!😉

https://bit.ly/3ChZWSz

📚The Cocktail Fork Problem: Three-Stem Audio Separation for Real-World Soundtracks

The cocktail party problem aims at isolating any source of interest within a complex acoustic scene, and has long inspired audio source separation research. Learn about the solution!

https://bit.ly/3qF6usi

💡Detect industrial defects at low latency with computer vision at the edge with Amazon SageMaker Edge

Learn how to create the cloud to edge solution with Amazon SageMaker to detect defective parts from a real-time stream of images sent to an edge device. A demo included.

https://go.aws/30ny7ea