🔥Hello friends!
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/3yMTe6L
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/3yMTe6L
📚NÜWA: Visual Synthesis Pre-training for Neural visUal World creAtion
NÜWA is a unified multimodal pre-trained model that can generate new or manipulate existing visual data (i.e., images and videos) for various visual synthesis tasks.
https://bit.ly/33Id9s9
NÜWA is a unified multimodal pre-trained model that can generate new or manipulate existing visual data (i.e., images and videos) for various visual synthesis tasks.
https://bit.ly/33Id9s9
⚡️Happy Monday, friends! Data Phoenix team wishes you an amazing week! Today, we want to present to you Tamara McCleary
Tamara is the founder and CEO of a global social media marketing agency, Thulium. Currently, she’s a full-time graduate student at Harvard. As a research scientist at the Harvard Kennedy School, she studies science, technology, ethics, global economics, and public policy.
Tamara is interested in algorithmic governance, as well as the social, moral, ethical, and spiritual implications of genetic engineering. She prefers exploring various existential questions, and the future of religion in the world where life extension technologies, synthetic biology, artificial general intelligence, and our reliance on machines create a transhumanist and post-humanist existence.
She is also an advisor and crew member for the Proudly Human Off-World Projects, which simulates resource-constrained environments in search of solutions for those living off-world.
https://bit.ly/3skl5db
Tamara is the founder and CEO of a global social media marketing agency, Thulium. Currently, she’s a full-time graduate student at Harvard. As a research scientist at the Harvard Kennedy School, she studies science, technology, ethics, global economics, and public policy.
Tamara is interested in algorithmic governance, as well as the social, moral, ethical, and spiritual implications of genetic engineering. She prefers exploring various existential questions, and the future of religion in the world where life extension technologies, synthetic biology, artificial general intelligence, and our reliance on machines create a transhumanist and post-humanist existence.
She is also an advisor and crew member for the Proudly Human Off-World Projects, which simulates resource-constrained environments in search of solutions for those living off-world.
https://bit.ly/3skl5db
💡Visualizing the vanishing gradient problem
In this tutorial, you'll learn why the vanishing gradient problem exists, including its 101, do's and don'ts, and all about configurations of neural networks susceptible to vanishing gradient.
https://bit.ly/3yHl6sQ
In this tutorial, you'll learn why the vanishing gradient problem exists, including its 101, do's and don'ts, and all about configurations of neural networks susceptible to vanishing gradient.
https://bit.ly/3yHl6sQ
Machine Learning Mastery
Visualizing the vanishing gradient problem - Machine Learning Mastery
Deep learning was a recent invention. Partially, it is due to improved computation power that allows us to use more layers of perceptrons in a neural network. But at the same time, we can train a deep network only after we know how to work around the vanishing…
📚GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training
GradInit is an automated and architecture agnostic method for initializing neural networks. It improves the stability of the original Transformer architecture for machine translation.
https://bit.ly/3pbIRX0
GradInit is an automated and architecture agnostic method for initializing neural networks. It improves the stability of the original Transformer architecture for machine translation.
https://bit.ly/3pbIRX0
📌Meta-Learning for Keyphrase Extraction
This article explores how to build a key phrase extractor that performs on in-domain data and in zero-shot scenarios where keyphrases need to be extracted from data with different distributions.
https://bit.ly/32sN3J6
This article explores how to build a key phrase extractor that performs on in-domain data and in zero-shot scenarios where keyphrases need to be extracted from data with different distributions.
https://bit.ly/32sN3J6
Medium
Meta-Learning for Keyphrase Extraction
A strategy to boost zero-shot predictions
📚End-to-End Referring Video Object Segmentation with Multimodal Transformers
This paper presents Multimodal Tracking Transformer (MTTR) that models the RVOS task as a sequence prediction problem. It simplifies the RVOS pipeline compared to existing methods.
https://bit.ly/3H85LVq
This paper presents Multimodal Tracking Transformer (MTTR) that models the RVOS task as a sequence prediction problem. It simplifies the RVOS pipeline compared to existing methods.
https://bit.ly/3H85LVq
⚡️Hello everyone!
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/3ElROBu
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/3ElROBu
Data Phoenix
Data Phoenix is your best friend in learning and growing in the data world! We publish digest, organize events and help expand the frontiers of your knowledge in ML, CV, NLP, and other aspects of AI.
💡Accelerating Inference Up to 6x Faster in PyTorch with Torch-TensorRT
Torch-TensorRT is the new integration of PyTorch with NVIDIA TensorRT, which accelerates the inference with one line of code. Learn how you can start using it today!
https://bit.ly/3eqGY2g
Torch-TensorRT is the new integration of PyTorch with NVIDIA TensorRT, which accelerates the inference with one line of code. Learn how you can start using it today!
https://bit.ly/3eqGY2g
NVIDIA Developer Blog
Accelerating Inference Up to 6x Faster in PyTorch with Torch-TensorRT | NVIDIA Developer Blog
Torch-TensorRT is a PyTorch integration for TensorRT inference optimizations on NVIDIA GPUs. With just one line of code, it speeds up performance up to 6x.
🎄This is the most magical period of the year!
So, even if you are a hardcore science guy, let’s give each other a chance to believe in something special! Data Phoenix team wishes you health, peace, love, and joy this holiday season and throughout 2022. We appreciate every single one of you and we hope that in 2022 we would expand our family of data enthusiasts even more.
❄️Merry Christmas and Happy New Year!
So, even if you are a hardcore science guy, let’s give each other a chance to believe in something special! Data Phoenix team wishes you health, peace, love, and joy this holiday season and throughout 2022. We appreciate every single one of you and we hope that in 2022 we would expand our family of data enthusiasts even more.
❄️Merry Christmas and Happy New Year!
💥Hello everyone! Data Phoenix Speaking!
We are 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/3qlzVO4
We are 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/3qlzVO4
Data Phoenix
Data Phoenix Digest - ISSUE 37
Data Phoenix team looking for speakers, unsupervised anomaly detection in Python, GAN training challenges, Player of Games, GAN-Supervised dense visual alignment, NeRF, ICON, SeqFormer, videos, jobs, and more ...
📚Donut: Document Understanding Transformer without OCR
Donut is a novel VDU model that is end-to-end trainable without OCR framework designed to pre-train the model to mitigate the dependencies on large-scale real document images.
https://bit.ly/3FrukMs
Donut is a novel VDU model that is end-to-end trainable without OCR framework designed to pre-train the model to mitigate the dependencies on large-scale real document images.
https://bit.ly/3FrukMs
⚡️Hello everyone & Merry Christmas!
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) Machine Learning architect - SoftServe (Odesa, Kyiv, Lviv)
https://bit.ly/3poR6iC
2) Computer Vision Engineer - YouScan (Kyiv)
https://bit.ly/30WASDO
3) ML/CV Engineer - Samsung R&D Institute Ukraine (Kyiv)
https://bit.ly/32qURvd
4) Middle+/Senior Data scientist - Autodoc (Odesa, Kyiv, Remote)
https://bit.ly/3FujAgu
5) Senior Data Scientist - Capgemini Engineering (Odesa, Kyiv, Remote)
https://bit.ly/3Fs3NPd
📌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!
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) Machine Learning architect - SoftServe (Odesa, Kyiv, Lviv)
https://bit.ly/3poR6iC
2) Computer Vision Engineer - YouScan (Kyiv)
https://bit.ly/30WASDO
3) ML/CV Engineer - Samsung R&D Institute Ukraine (Kyiv)
https://bit.ly/32qURvd
4) Middle+/Senior Data scientist - Autodoc (Odesa, Kyiv, Remote)
https://bit.ly/3FujAgu
5) Senior Data Scientist - Capgemini Engineering (Odesa, Kyiv, Remote)
https://bit.ly/3Fs3NPd
📌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!
🔥Hello friends!
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/3Hii81j
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/3Hii81j
📌5 Anomaly Detection Algorithms every Data Scientist should know
There are many reasons for anomalies to occur in your dataset. In this article, you’ll find an overview and a comparison of the best anomaly detection algorithms for outlier detection.
https://bit.ly/3eux7J3
There are many reasons for anomalies to occur in your dataset. In this article, you’ll find an overview and a comparison of the best anomaly detection algorithms for outlier detection.
https://bit.ly/3eux7J3
Medium
5 Anomaly Detection Algorithms every Data Scientist should know
Comparing anomaly detection algorithms for Outlier detection
💫Happy Monday, friends! Let’s start our week in the company of Mike Quindazzi
He’s a managing director leading sales for US Digital Alliances at PwC. He’s been investing his time in gathering industry experience and crafting his management. He’s responsible for nurturing a $1.5 billion cross-sector digital practice by developing innovative approaches and resolving complex issues for clients.
Mike’s greatest reward is helping his clients grow by tapping into their competitive advantages whether that entails global expansion, accelerating digital growth, improving customer experience, transforming organizations, or implementing complex systems for HR/ERP.
He works with diverse & dynamic teams across a range of clients & tech alliances. Whether we think of an acquisition, a minority stake investment, or IPO, Mike focuses on creating value in each and every transaction. He scopes value through effective integration, unlocking synergies, and creating new structures.
https://bit.ly/3ExyaT9
He’s a managing director leading sales for US Digital Alliances at PwC. He’s been investing his time in gathering industry experience and crafting his management. He’s responsible for nurturing a $1.5 billion cross-sector digital practice by developing innovative approaches and resolving complex issues for clients.
Mike’s greatest reward is helping his clients grow by tapping into their competitive advantages whether that entails global expansion, accelerating digital growth, improving customer experience, transforming organizations, or implementing complex systems for HR/ERP.
He works with diverse & dynamic teams across a range of clients & tech alliances. Whether we think of an acquisition, a minority stake investment, or IPO, Mike focuses on creating value in each and every transaction. He scopes value through effective integration, unlocking synergies, and creating new structures.
https://bit.ly/3ExyaT9
📚Player of Games
Player of Games is the first algorithm to achieve strong empirical performance in large perfect and imperfect information games. It reaches strong performance in various games, from Go to poker.
https://bit.ly/3H87n1o
Player of Games is the first algorithm to achieve strong empirical performance in large perfect and imperfect information games. It reaches strong performance in various games, from Go to poker.
https://bit.ly/3H87n1o
💡Speech Recognition in Real-Time using Python
In this post, you’ll find a step-by-step guide explaining how to convert your speech to text in real-time using Python. Let’s learn more about live transcription together!
https://bit.ly/345ngrc
In this post, you’ll find a step-by-step guide explaining how to convert your speech to text in real-time using Python. Let’s learn more about live transcription together!
https://bit.ly/345ngrc
Medium
Speech Recognition in Real-Time using Python
Step-by-step Guide to Live Transcription
📚SeqFormer: a Frustratingly Simple Model for Video Instance Segmentation
SeqFormer is a simple model for video instance segmentation designed to follow the principle of vision transformer that models instance relationships among video frames.
https://bit.ly/3mF5ilS
SeqFormer is a simple model for video instance segmentation designed to follow the principle of vision transformer that models instance relationships among video frames.
https://bit.ly/3mF5ilS
🔥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
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
Data Phoenix
Data Phoenix is your best friend in learning and growing in the data world! We publish digest, organize events and help expand the frontiers of your knowledge in ML, CV, NLP, and other aspects of AI.
👍1
🎥 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
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
YouTube
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis (ML Research Paper Explained)
#nerf #neuralrendering #deeplearning
View Synthesis is a tricky problem, especially when only given a sparse set of images as an input. NeRF embeds an entire scene into the weights of a feedforward neural network, trained by backpropagation through a differential…
View Synthesis is a tricky problem, especially when only given a sparse set of images as an input. NeRF embeds an entire scene into the weights of a feedforward neural network, trained by backpropagation through a differential…