💡Data Movement in Netflix Studio via Data Mesh
Learn about Netflix's journey to a more efficient data movement using Data Mesh, to improve the pace of production and efficiency of global business operations using the most up-to-date information.
https://bit.ly/3yWUV0R
Learn about Netflix's journey to a more efficient data movement using Data Mesh, to improve the pace of production and efficiency of global business operations using the most up-to-date information.
https://bit.ly/3yWUV0R
Medium
Data Movement in Netflix Studio via Data Mesh
By Andrew Nguonly, Armando Magalhães, Obi-Ike Nwoke, Shervin Afshar, Sreyashi Das, Tongliang Liu, Wei Liu, Yucheng Zeng
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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.
📌Observation of Time-Crystalline Eigenstate Order on a Quantum Processor
The authors demonstrate the characteristic spatiotemporal response of a DTC for generic initial states. A time-reversal protocol discriminates external decoherence from intrinsic thermalization and uses quantum typicality to circumvent the cost of densely sampling the eigenspectrum.
https://bit.ly/3CTIBRn
The authors demonstrate the characteristic spatiotemporal response of a DTC for generic initial states. A time-reversal protocol discriminates external decoherence from intrinsic thermalization and uses quantum typicality to circumvent the cost of densely sampling the eigenspectrum.
https://bit.ly/3CTIBRn
The latest issue of the digest is already waiting for you on our website! Tap on the link and feel free to subscribe 👇🏻
https://bit.ly/2W9Iss8
https://bit.ly/2W9Iss8
Data Phoenix
Data Phoenix Digest - 19.08.2021
Webinar "The A-Z of Data: Monitoring ML Models in Production"; AI for food security, road safety, and agriculture efficiency; introducing Droidlet; all probability distributions explained in six minutes; make money using NFT + AI; Perceiver IO, SPEAR, SDEdit…
💡Make Money Using NFT + AI | GAN Image Generation
In this article, you'll see how to create new images using GAN, with a focus on generating art using Stylegan2-ADA. The goal is to create contemporary art via NFT and sell it via Opeansea.
https://bit.ly/2We6xhD
In this article, you'll see how to create new images using GAN, with a focus on generating art using Stylegan2-ADA. The goal is to create contemporary art via NFT and sell it via Opeansea.
https://bit.ly/2We6xhD
Medium
Make money using NFT + AI | GAN image generation
Create images using AI and sell it via NFT
The Data Phoenix Events team invites you all on August 25 to the second of our series of "The A-Z of Data" webinars. The topic — Monitoring ML Models in Production.
The performance of machine learning models can decline over time - due to changes in data, business processes, or simply data loss or failures. To avoid the negative impact on business performance, it is crucial to detect such situations and take timely action - for example, by retraining the model. Due to this, monitoring of services based on machine learning needs to include additional metrics related to the model and data quality. In the course of the tutorial, Emeli Dral will demonstrate how the quality of a model can change over time, and how one can track and analyze the changes using open source tools.
Participation is free, but pre-registration is required.
https://bit.ly/3giNlq0
The performance of machine learning models can decline over time - due to changes in data, business processes, or simply data loss or failures. To avoid the negative impact on business performance, it is crucial to detect such situations and take timely action - for example, by retraining the model. Due to this, monitoring of services based on machine learning needs to include additional metrics related to the model and data quality. In the course of the tutorial, Emeli Dral will demonstrate how the quality of a model can change over time, and how one can track and analyze the changes using open source tools.
Participation is free, but pre-registration is required.
https://bit.ly/3giNlq0
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.
We are aware that some of you are looking for job opportunities. We've put together a list of 10 positions available this week, enjoy!
1) Data Engineer, Appian
https://bit.ly/382oi66
2) Applied Scientist II - ML/NLP, Amazon
https://bit.ly/382s5jz
3) Data Scientist - Analytics, Host Quality, Airbnb
https://bit.ly/3sCRRVk
4) Principal Data Scientist, Atlassian
https://bit.ly/3y6XcFn
5) Machine Learning Scientist, Amazon
https://bit.ly/3AZRiry
For other 5 positions click 👉🏻 https://bit.ly/3mrxwkq
Did you find something for yourself? Let us know!
1) Data Engineer, Appian
https://bit.ly/382oi66
2) Applied Scientist II - ML/NLP, Amazon
https://bit.ly/382s5jz
3) Data Scientist - Analytics, Host Quality, Airbnb
https://bit.ly/3sCRRVk
4) Principal Data Scientist, Atlassian
https://bit.ly/3y6XcFn
5) Machine Learning Scientist, Amazon
https://bit.ly/3AZRiry
For other 5 positions click 👉🏻 https://bit.ly/3mrxwkq
Did you find something for yourself? Let us know!
💡Geometric Foundations of Deep Learning
Geometric Deep Learning is an attempt for geometric unification of a broad class of ML problems from the perspectives of symmetry and invariance. Explore the topic in detail!
https://bit.ly/3B5o4rn
Geometric Deep Learning is an attempt for geometric unification of a broad class of ML problems from the perspectives of symmetry and invariance. Explore the topic in detail!
https://bit.ly/3B5o4rn
Medium
Geometric foundations of Deep Learning
Geometric Deep Learning is an attempt to unify a broad class of ML problems from the perspectives of symmetry and invariance.
📌Using Sentiment Score to Assess Customer Service Quality
Net Promoter Score (NPS) is a well-accepted measurement of customer satisfaction in most customer-facing industries. In this article, you'll learn how Airbnb uses ML to calculate it.
https://bit.ly/380T66X
Net Promoter Score (NPS) is a well-accepted measurement of customer satisfaction in most customer-facing industries. In this article, you'll learn how Airbnb uses ML to calculate it.
https://bit.ly/380T66X
Medium
Using Sentiment Score to Assess Customer Service Quality
How AI-based Sentiment Models Complement Net Promoter Score
💡Feature Store: Data Platform for Machine Learning
Feature data is critical to the accurate predictions made by ML models. In this article, you'll learn how to generate, manage, and serve features by using open-source and homegrown feature stores.
https://bit.ly/3mplpEH
Feature data is critical to the accurate predictions made by ML models. In this article, you'll learn how to generate, manage, and serve features by using open-source and homegrown feature stores.
https://bit.ly/3mplpEH
Medium
Feature Store: Data Platform for Machine Learning
State-of-the-art open-source and homegrown feature stores that generate, manage and serve features at scale
Hello friends! The Data Phoenix team wants to remind you about the upcoming event on August 25. It is the second of our series of "The A-Z of Data" webinars.
The topic — Monitoring ML Models in Production
Welcome our speaker! Emeli Dral is a Co-founder and CTO at Evidently AI, a startup developing open-source tools to analyze and monitor the performance of machine learning models. Earlier, she co-founded an industrial AI startup and served as the Chief Data Scientist at Yandex Data Factory. She led over 50 applied ML projects for various industries - from banking to manufacturing. Emeli is a data science lecturer at GSOM SpBU and Harbour. Space University. She is a co-author of the Machine Learning and Data Analysis curriculum at Coursera with over 100,000 students. She also co-founded Data Mining in Action, the largest open data science course in Russia. Emeli will demonstrate how the quality of a model can change over time, and how one can track and analyze the changes using open source tools.
https://bit.ly/2WfhgbC
The topic — Monitoring ML Models in Production
Welcome our speaker! Emeli Dral is a Co-founder and CTO at Evidently AI, a startup developing open-source tools to analyze and monitor the performance of machine learning models. Earlier, she co-founded an industrial AI startup and served as the Chief Data Scientist at Yandex Data Factory. She led over 50 applied ML projects for various industries - from banking to manufacturing. Emeli is a data science lecturer at GSOM SpBU and Harbour. Space University. She is a co-author of the Machine Learning and Data Analysis curriculum at Coursera with over 100,000 students. She also co-founded Data Mining in Action, the largest open data science course in Russia. Emeli will demonstrate how the quality of a model can change over time, and how one can track and analyze the changes using open source tools.
https://bit.ly/2WfhgbC
📌GPU-Powered Data Science (NOT Deep Learning) with RAPIDS
Tired of the deep learning hype? In this article, you'll learn how to utilize GPUs for regular data science and machine learning even if you don't lots of deep learning work.
https://bit.ly/3BbNQu1
Tired of the deep learning hype? In this article, you'll learn how to utilize GPUs for regular data science and machine learning even if you don't lots of deep learning work.
https://bit.ly/3BbNQu1
Medium
GPU-Powered Data Science (NOT Deep Learning) with RAPIDS
How to utilize the power of your GPU for regular data science and machine learning even if you do not do a lot of deep learning work.
Data Phoenix is proud to be a Ukrainian team and today we celebrate 30 years of independence of our motherland. Join us!
Happy Independence Day of Ukraine! 🇺🇦
Happy Independence Day of Ukraine! 🇺🇦
💡Moving SciPy to the Meson Build System
In this guide, you'll learn about moving SciPy to Meson. Because SciPy now builds with Meson on Linux, it's worth exploring: expect faster builds and a more pleasant development experience.
https://bit.ly/38dUUJX
In this guide, you'll learn about moving SciPy to Meson. Because SciPy now builds with Meson on Linux, it's worth exploring: expect faster builds and a more pleasant development experience.
https://bit.ly/38dUUJX
Quansight Labs
Moving SciPy to the Meson build system
Let's start with an announcement: SciPy now builds with
Meson on Linux, and the full test suite passes!
This is a pretty exciting milestone, and good news for SciPy maintainers and
contributors - they
Meson on Linux, and the full test suite passes!
This is a pretty exciting milestone, and good news for SciPy maintainers and
contributors - they
Friendly reminder that tomorrow you will receive our weekly newsletter, if you didn't subscribe don't waste your time! 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 friends!
https://bit.ly/3jeZD4w
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Data Phoenix
SF Bay Area media and education platform focused on AI and Data. As a voice of AI industry, Data Phoenix delivers news, practical knowledge, and helps companies be heard in the community.
📌Semi-Supervising Learning, Transfer Learning, and Knowledge Distillation with SimCLR
Khoi Nguyen et al. conduct analyses on three different aspects of SimCLR to analyze properties of contrast learning on fine-tuning, research knowledge distillation through teacher-forcing paradigm and study how transfer learning works on various datasets.
https://bit.ly/38cHRIX
Khoi Nguyen et al. conduct analyses on three different aspects of SimCLR to analyze properties of contrast learning on fine-tuning, research knowledge distillation through teacher-forcing paradigm and study how transfer learning works on various datasets.
https://bit.ly/38cHRIX
The latest issue of the digest is already waiting for you on our website! Tap on the link and feel free to subscribe 👇🏻
https://bit.ly/3sTKMj5
https://bit.ly/3sTKMj5
Data Phoenix
Data Phoenix Digest - 26.08.2021
Announcement of next three webinars of "The A-Z of Data" series, AI and social sciences, MLOps best practices for Data Scientists, bootstrapping labels via supervision & Human-In-The-Loop, Machine Learning Zoomcamp, papers, videos, courses, jobs, and more...
💡SSWL-IDN: Self-Supervised CT Denoising
In this article, Ayaan Hague provides an explanation of SSWL-IDN that leverages residual learning and a hybrid loss combining perceptual loss and MSE, all incorporated in a VAE framework.
https://bit.ly/3mzbs7P
In this article, Ayaan Hague provides an explanation of SSWL-IDN that leverages residual learning and a hybrid loss combining perceptual loss and MSE, all incorporated in a VAE framework.
https://bit.ly/3mzbs7P
Medium
SSWL-IDN: Self-Supervised CT Denoising
A review of our recent CT Denoising paper “Window-Level is a Strong Denoising Surrogate”
We know that some of you are looking for job opportunities. Here is a list of 10 positions available this week, enjoy!
1) Machine Learning Engineer, Shelf
https://bit.ly/2WqvaaI
2) Data Scientist, Shelf
https://bit.ly/3zmOhRv
3) Senior/Middle CV/ML Engineer, Apostera
https://bit.ly/2Wuhyeq
4) Senior Data Scientist for Sport Stream, Parimatch Tech
https://bit.ly/38fPEpg
5) Data Scientist (NLP), SoftServe
https://bit.ly/3ks18vv
For other 5 positions click 👉🏻 https://bit.ly/3mKTtuW
Did you find something for yourself? Let us know!
1) Machine Learning Engineer, Shelf
https://bit.ly/2WqvaaI
2) Data Scientist, Shelf
https://bit.ly/3zmOhRv
3) Senior/Middle CV/ML Engineer, Apostera
https://bit.ly/2Wuhyeq
4) Senior Data Scientist for Sport Stream, Parimatch Tech
https://bit.ly/38fPEpg
5) Data Scientist (NLP), SoftServe
https://bit.ly/3ks18vv
For other 5 positions click 👉🏻 https://bit.ly/3mKTtuW
Did you find something for yourself? Let us know!
📌How to Train a BERT Model From Scratch
A BERT 101. In this article, you'll find a step-by-step guide to training a functional model from scratch. All guidelines are clear and will work well for beginners.
https://bit.ly/3zpXWqC
A BERT 101. In this article, you'll find a step-by-step guide to training a functional model from scratch. All guidelines are clear and will work well for beginners.
https://bit.ly/3zpXWqC
Medium
How to Train a BERT Model From Scratch
Meet BERT’s Italian cousin, FiliBERTo