Data Phoenix

2022-01-04 10:00:04 Distillation of BERT-Like Models: The Theory

Let’s explore the mechanisms behind the approach of DistilBERT, including 101, architectures, distillation loss, and other useful details you may need in your implementation.

https://bit.ly/3JyAcpP Open / Comment

2022-01-03 16:00:09 ​​ Hello friends! Let's take a look at Yann LeCun. He is best known for his work in deep learning and the invention of the convolutional network method which is widely used for image, video, and speech recognition.

He is VP and Chief AI Scientist at Facebook and Silver Professor at NYU affiliated with the Courant Institute and the Center for Data Science. Yann was the founding Director of Facebook AI Research and of the NYU Center for Data Science.

In late 2013, LeCun became Director of AI Research at Facebook, while remaining on the NYU Faculty part-time. His research interests include machine learning and artificial intelligence, with applications to computer vision, natural language understanding, robotics, and computational neuroscience. He is the recipient of the 2018 ACM Turing Award for "conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing".

https://bit.ly/3sUgEGq Open / Comment

2022-01-03 10:00:05 Ensembling Off-the-shelf Models for GAN Training

Nupur Kumari et al. propose an effective selection mechanism for pretrained CV models. It allows to choose the most accurate model, and progressively add it to the discriminator ensemble.

https://bit.ly/3JBmuSR Open / Comment

2022-01-02 16:00:04 Paper Review: NL-Augmenter A Framework for Task-Sensitive Natural Language Augmentation

This paper review shares a look at a new participatory Python-based natural language augmentation framework that supports the creation of transformations and filters.

https://bit.ly/3HtXXgN Open / Comment

2022-01-02 10:00:08 ​​ Hello everybody!
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/3mPEEXh Open / Comment

2022-01-01 16:00:07 ​​ Hello everyone!
We hope that your year started 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) Major Donor Data Specialist - Wikimedia Foundation (Remote)
https://bit.ly/32OYn2g
2) Sr. Data Engineer - HashiCorp (US - Remote)
https://bit.ly/3mMKAk5
3) Machine Learning Architect - SoftServe (Odesa, Kyiv, Lviv...)
https://bit.ly/3EIQA3q
4) Senior/Middle CV/ML Engineer - Apostera (Odesa, Kyiv, Remote)
https://bit.ly/3eIrqr8
5) Data Scientist - Snap (Odesa, Kyiv)
https://bit.ly/3eIjSEw

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! Open / Comment

2022-01-01 10:00:05 Unsupervised Anomaly Detection in Python

Why’s it so important for data scientists to master anomaly detection? Check out this beginner’s guide to learn all the ins and outs of unsupervised anomaly detection.

https://bit.ly/3sOvQ7Z Open / Comment

2021-12-31 14:00:03 Hello friends!
Data Phoenix team congratulates everyone with the coming New 2022 year!
We are ready to present our weekly issue of the digest - the last one this year! And it is already waiting for you on our website! Tap on the link and feel free to subscribe
https://bit.ly/3FNjBfy Open / Comment

2021-12-31 10:00:05 NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

View Synthesis is a tricky problem. Learn how NeRF embeds an entire scene into the weights of a feedforward neural network to achieve state-of-the-art view synthesis.

https://bit.ly/3Jxy0Pm Open / Comment

2021-12-30 16:00:03 Hello friends!

We hope that your week is going well so far. Data Phoenix team wants to remind you about our weekly newsletter which is coming, as always, 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/3FJCn7v Open / Comment