📚Alias-Free Generative Adversarial Networks
The researchers trace the root cause to careless signal processing that causes aliasing in the generator network and derive architectural changes that guarantee better results.
https://bit.ly/3qHf6ys
The researchers trace the root cause to careless signal processing that causes aliasing in the generator network and derive architectural changes that guarantee better results.
https://bit.ly/3qHf6ys
📌Training a DCGAN in PyTotch
In this tutorial, you'll learn how to train our first DCGAN Model using PyTorch to generate images. Check out Part 2 and Part 3 of the series
on Advanced PyTorch Techniques.
https://bit.ly/3qOyRUU
In this tutorial, you'll learn how to train our first DCGAN Model using PyTorch to generate images. Check out Part 2 and Part 3 of the series
on Advanced PyTorch Techniques.
https://bit.ly/3qOyRUU
PyImageSearch
Training a DCGAN in PyTorch - PyImageSearch
Learn to train a DCGAN using PyTorch and Python. This tutorial is perfect for coders comfortable with PyTorch and Generative Adversarial Networks.
⚡️Hello everyone, 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/3nt5QMd
https://bit.ly/3nt5QMd
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.
This media is not supported in your browser
VIEW IN TELEGRAM
Join Dr. Dean and Dr. Bazhirov on November 19th to learn more about Interpretable Machine Learning for materials research and development.
==
The exponential growth of interest in Machine Learning has led to a wealth of data in recent years, which has corresponded with an expansion in the number of techniques available. In this webinar, we benchmark a few recent techniques, including SISSO (Symbolic Regression), TPOT (AutoML), Roost (deep learning algorithms), and XGBoost (Gradient-boosting) to predict the properties of perovskites and 2dmaterials.
Register at https://bit.ly/3nuAp4h
==
The exponential growth of interest in Machine Learning has led to a wealth of data in recent years, which has corresponded with an expansion in the number of techniques available. In this webinar, we benchmark a few recent techniques, including SISSO (Symbolic Regression), TPOT (AutoML), Roost (deep learning algorithms), and XGBoost (Gradient-boosting) to predict the properties of perovskites and 2dmaterials.
Register at https://bit.ly/3nuAp4h
💡Serving ML Models in Production: Common Patterns
This article explores Ray Serve, a service combining pipelines, ensemble, business logic, and online learning for machine learning. Learn how to use the service for serving ML models in production.
https://bit.ly/3criUeG
This article explores Ray Serve, a service combining pipelines, ensemble, business logic, and online learning for machine learning. Learn how to use the service for serving ML models in production.
https://bit.ly/3criUeG
Anyscale
Serving ML Models in Production: Common Patterns | Anyscale
In this post, we explore the 4 common patterns of ML in production and how to implement these patterns using Ray Serve.
⚡️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/3x40Q47
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/3x40Q47
Data Phoenix
Data Phoenix Digest - ISSUE 32
NVIDIA's Omniverse and BMW, industrial data revolution, AI trends for 2022, K-Means clustering explained, AutoML, EditGAN, DScribe, CFPNet, StyleCLIPDraw, jobs, and more ...
⚡️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) JS Engineer (Meteor+React) at Exabyte.io - please write to d.spodarets@dataphoenix.info directly
2) Software Engineer, Machine Learning at Grammarly (San Francisco; Remote).
https://bit.ly/3oOqRQW
3) Machine Learning Engineer at Amazon (Santa Clara, California, USA).
https://bit.ly/3Fzcln6
4) Machine Learning Engineer at Twilio (Madrid, Spain).
https://bit.ly/3CMAmFz
5) Machine Learning Scientist, Core AI at Amazon (Berlin, Germany).
https://bit.ly/3CA0svf
Looking to feature your open positions in the digest? Kindly reach out to us at editor@dataphoenix.info
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) JS Engineer (Meteor+React) at Exabyte.io - please write to d.spodarets@dataphoenix.info directly
2) Software Engineer, Machine Learning at Grammarly (San Francisco; Remote).
https://bit.ly/3oOqRQW
3) Machine Learning Engineer at Amazon (Santa Clara, California, USA).
https://bit.ly/3Fzcln6
4) Machine Learning Engineer at Twilio (Madrid, Spain).
https://bit.ly/3CMAmFz
5) Machine Learning Scientist, Core AI at Amazon (Berlin, Germany).
https://bit.ly/3CA0svf
Looking to feature your open positions in the digest? Kindly reach out to us at editor@dataphoenix.info
📌Solving Math Word Problems
Learn about a system trained by the OpenAI team that solves grade school math problems with twice the accuracy of a fine-tuned GPT-3 model. It solves ~90% as many problems as real kids.
https://bit.ly/30KA5oX
Learn about a system trained by the OpenAI team that solves grade school math problems with twice the accuracy of a fine-tuned GPT-3 model. It solves ~90% as many problems as real kids.
https://bit.ly/30KA5oX
Openai
Solving math word problems
We’ve trained a system that solves grade school math problems with nearly twice the accuracy of a fine-tuned GPT-3 model. It solves about 90% as many problems as real kids: a small sample of 9-12 year olds scored 60% on a test from our dataset, while our…
🔥Data Phoenix wishes you lovely Sunday! We hope 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/3HQC4cG
But first things first, here's your weekly dose of positivity🤗
https://bit.ly/3HQC4cG
📚EditGAN: High-Precision Semantic Image Editing
EditGAN is a novel method for high quality, high precision semantic image editing, allowing users to edit images by modifying their highly detailed part segmentation masks.
https://bit.ly/3cvlAIu
EditGAN is a novel method for high quality, high precision semantic image editing, allowing users to edit images by modifying their highly detailed part segmentation masks.
https://bit.ly/3cvlAIu
⚡️Hello everyone! How are you feeling about starting a new week? Today, let us introduce you Bernard Marr — a world-renowned futurist, influencer, and thought leader in business and technology. Passionate about using technology for the good of humanity, he shares his vision with over 2 million social media followers and 1 million newsletter subscribers. He was ranked by LinkedIn as one of the top 5 business influencers in the world and the No.1 influencer in the UK.
Today, Bernard Marr is one of the world’s most highly respected experts when it comes to future trends, strategy, business performance, digital transformation, and the intelligent use of data and AI in business. He has worked with and advised many of the world’s best-known organizations, such as Amazon, Google, Microsoft, Astra Zeneca, The Bank of England, BP, NVIDIA, Cisco, DHL, IBM, HPE, Ericsson, Jaguar Land Rover, Mars, The Ministry of Defense, NATO, The Home Office, NHS, Oracle, T-Mobile, Toyota, The Royal Air Force, Shell, The United Nations, Walgreens Alliance Boots, and Walmart.
He is the author of 20 books and hundreds of high profile reports and articles, including the international best-sellers. His books have been translated into over 20 languages and have been repeatedly featured as the Amazon No.1 bestselling book. He has earned the CMI Management Book of the Year award, the Axiom book award, and the WHSmith best business book award.
Today, Bernard also enjoys teaching for Oxford University, Warwick Business School, the Irish Management Institute, and ICAEW. On top of that, Bernard serves as a non-executive director on the board of businesses and has a seat on the dean’s council for Lancaster University Management School.
https://bit.ly/3qXZAOF
Today, Bernard Marr is one of the world’s most highly respected experts when it comes to future trends, strategy, business performance, digital transformation, and the intelligent use of data and AI in business. He has worked with and advised many of the world’s best-known organizations, such as Amazon, Google, Microsoft, Astra Zeneca, The Bank of England, BP, NVIDIA, Cisco, DHL, IBM, HPE, Ericsson, Jaguar Land Rover, Mars, The Ministry of Defense, NATO, The Home Office, NHS, Oracle, T-Mobile, Toyota, The Royal Air Force, Shell, The United Nations, Walgreens Alliance Boots, and Walmart.
He is the author of 20 books and hundreds of high profile reports and articles, including the international best-sellers. His books have been translated into over 20 languages and have been repeatedly featured as the Amazon No.1 bestselling book. He has earned the CMI Management Book of the Year award, the Axiom book award, and the WHSmith best business book award.
Today, Bernard also enjoys teaching for Oxford University, Warwick Business School, the Irish Management Institute, and ICAEW. On top of that, Bernard serves as a non-executive director on the board of businesses and has a seat on the dean’s council for Lancaster University Management School.
https://bit.ly/3qXZAOF
Bernard Marr
Bernard Marr | Future . Business . Success
Influencer
Bernard Marr is one of the world’s most successful social media influencers at the intersection of business and technology. View More
Keynote Speaker
Bernard Marr is a popular keynote choice because of his vast practical experience…
Bernard Marr is one of the world’s most successful social media influencers at the intersection of business and technology. View More
Keynote Speaker
Bernard Marr is a popular keynote choice because of his vast practical experience…
💡Hugging Face Transformer Inference Under 1 Millisecond Latency
Hugging Face has released “Infinity’’, a server product that performs inference at enterprise scale. It can perform Transformer inference at 1 millisecond latency on the GPU.
https://bit.ly/3xb5Qnj
Hugging Face has released “Infinity’’, a server product that performs inference at enterprise scale. It can perform Transformer inference at 1 millisecond latency on the GPU.
https://bit.ly/3xb5Qnj
Medium
Hugging Face Transformer Inference Under 1 Millisecond Latency
Go to production with Microsoft and Nvidia open source tooling
📚 On the Frequency Bias of Generative Models
In this paper, the authors provide insights on measures against high-frequency artifacts and what makes them effective, with focus on a frequency bias.
https://bit.ly/3l1m51k
In this paper, the authors provide insights on measures against high-frequency artifacts and what makes them effective, with focus on a frequency bias.
https://bit.ly/3l1m51k
📌Design patterns for Machine Learning Pipelines
ML pipeline design keeps evolving. In this article, you'll learn how these design patterns changed, what processes they went through, and their future direction.
https://bit.ly/32nIRKp
ML pipeline design keeps evolving. In this article, you'll learn how these design patterns changed, what processes they went through, and their future direction.
https://bit.ly/32nIRKp
KDnuggets
Design Patterns for Machine Learning Pipelines
ML pipeline design has undergone several evolutions in the past decade with advances in memory and processor performance, storage systems, and the increasing scale of data sets. We describe how these design patterns changed, what processes they went through…
📚DScribe: Library of Denoscriptors for Machine Learning in Materials Science
DScribe is a software package for ML that provides "denoscriptors" for atomistic materials simulations, to accelerate and simplify the application of ML for atomistic property prediction.
https://bit.ly/3cKVMIe
DScribe is a software package for ML that provides "denoscriptors" for atomistic materials simulations, to accelerate and simplify the application of ML for atomistic property prediction.
https://bit.ly/3cKVMIe
🔥Hello friends! We hope that your week is going well this 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/3oYT6g7
https://bit.ly/3oYT6g7
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.
💡ORDAINED: The Python Project Template
Creating Python packages can be annoying. Learn about a project boilerplate template for Python packages that can be used instead of copying a directory tree and doing find and replace.
https://bit.ly/3xsJGxg'
Creating Python packages can be annoying. Learn about a project boilerplate template for Python packages that can be used instead of copying a directory tree and doing find and replace.
https://bit.ly/3xsJGxg'
TODO ...
🙏 ORDAINED: The Python Project Template
Creating a Cookiecutter template for generating opinionated Python project boilerplate.
📌How to Handle ML Model Drift in Production
Data drift is an everyday challenge in Data Science and Machine Learning. In this introductory overview, you'll learn about major steps you can take to handle it more efficiently.
https://bit.ly/3E12yFT
Data drift is an everyday challenge in Data Science and Machine Learning. In this introductory overview, you'll learn about major steps you can take to handle it more efficiently.
https://bit.ly/3E12yFT
Evidentlyai
"My data drifted. What's next?" How to handle ML model drift in production.
What can you do once you detect data drift for a production ML model? Here is an introductory overview of the possible steps.
⚡️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/3CWZlpB
https://bit.ly/3CWZlpB
Data Phoenix
Data Phoenix Digest - ISSUE 33
Instant access to OpenAI’s API. The perks of AI and automation. What Is the difference between outlier detection and data drift detection? PyTorch C++ API for use on mobile platforms. Compositional transformers for scene generation. CleanRL, Causal-BALD,…
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/3nZuC6V
But first things first, here's your weekly dose of positivity🤗
https://bit.ly/3nZuC6V
⚡️Hello friends!
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) Senior/Middle CV/ML Engineer at Apostera (Odesa, Kyiv, Remote)
https://bit.ly/3d0WOQs
2) Junior CV/ML Engineer at Apostera (Odesa, Kyiv, Remote)
https://bit.ly/3d0WOQs
3) Senior Data Scientist/ML Engineer at Xenoss (Odesa, Kyiv, Remote)
https://bit.ly/3I0pszG
4) Middle+/Senior Data scientist at AUTODOC (Odesa)
https://bit.ly/3IaIZxw
5) Machine Learning Architect at SoftServe (Odesa, Kyiv, Remote)
https://bit.ly/3lcoPcE
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!
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) Senior/Middle CV/ML Engineer at Apostera (Odesa, Kyiv, Remote)
https://bit.ly/3d0WOQs
2) Junior CV/ML Engineer at Apostera (Odesa, Kyiv, Remote)
https://bit.ly/3d0WOQs
3) Senior Data Scientist/ML Engineer at Xenoss (Odesa, Kyiv, Remote)
https://bit.ly/3I0pszG
4) Middle+/Senior Data scientist at AUTODOC (Odesa)
https://bit.ly/3IaIZxw
5) Machine Learning Architect at SoftServe (Odesa, Kyiv, Remote)
https://bit.ly/3lcoPcE
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!