Hey friends!
We would like to remind you about our YouTube channel where you can find all the footage from our latest events. Data Phoenix team understands that there are special circumstances that can make you miss our live event. That's why we uploaded all the videos online so you can watch them later and don't miss a thing! Tap the link and enjoy!
https://bit.ly/2XHYGJF
We would like to remind you about our YouTube channel where you can find all the footage from our latest events. Data Phoenix team understands that there are special circumstances that can make you miss our live event. That's why we uploaded all the videos online so you can watch them later and don't miss a thing! Tap the link and enjoy!
https://bit.ly/2XHYGJF
📌LightAutoML: AutoML Solution for a Large Financial Services Ecosystem
LightAutoML is an AutoML system developed for a large European financial services company and that has already been deployed in numerous applications. The paper presents an overview of it.
https://bit.ly/3zF22uq
LightAutoML is an AutoML system developed for a large European financial services company and that has already been deployed in numerous applications. The paper presents an overview of it.
https://bit.ly/3zF22uq
We are aware that some of you are looking for job opportunities. Here is a small list of positions available this week, enjoy!
1) Computational Materials Scientist AI/ML – Exabyte.io , San Francisco, Remote
https://bit.ly/3EUacTc
2) Junior Data Engineer – MoonPay, Remote (Europe)
https://bit.ly/3ENSMb0
3) Data Scientist – CB Insights, New York or Remote
https://bit.ly/3lSrkQK
4) Principal Software Engineer – Machine Learning – Twilio, Remote(US)
https://bit.ly/3uckBoy
5) Senior Data Engineer – 1Password, Remote (US or Canada)
https://bit.ly/39EM5cS
Did you find something for yourself? Let us know!
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!
1) Computational Materials Scientist AI/ML – Exabyte.io , San Francisco, Remote
https://bit.ly/3EUacTc
2) Junior Data Engineer – MoonPay, Remote (Europe)
https://bit.ly/3ENSMb0
3) Data Scientist – CB Insights, New York or Remote
https://bit.ly/3lSrkQK
4) Principal Software Engineer – Machine Learning – Twilio, Remote(US)
https://bit.ly/3uckBoy
5) Senior Data Engineer – 1Password, Remote (US or Canada)
https://bit.ly/39EM5cS
Did you find something for yourself? Let us know!
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!
💡How to Create an AutoML Pipeline Optimization Sandbox
In this article, we'll look into the ways and methods of implementing an automated machine learning pipeline optimization sandbox web app using Streamlit and TPOT.
https://bit.ly/39CiCR1
In this article, we'll look into the ways and methods of implementing an automated machine learning pipeline optimization sandbox web app using Streamlit and TPOT.
https://bit.ly/39CiCR1
📌Revisiting 3D ResNets for Video Recognition
In this paper, the researchers explore training and scaling strategies for video recognition models and propose a simple scaling strategy for 3D ResNets.
https://bit.ly/2ZzeSxU
In this paper, the researchers explore training and scaling strategies for video recognition models and propose a simple scaling strategy for 3D ResNets.
https://bit.ly/2ZzeSxU
💡Supercharge Image Classification with Transfer Learning
Hop in to learn how to leverage pretrained ResNets from Tensorflow-Hub to take advantage of their ability to be easily transfer-learnt/fine-tuned on new datasets.
https://bit.ly/2XYcQXN
Hop in to learn how to leverage pretrained ResNets from Tensorflow-Hub to take advantage of their ability to be easily transfer-learnt/fine-tuned on new datasets.
https://bit.ly/2XYcQXN
Towards Data Science
Supercharge Image Classification with Transfer Learning | Towards Data Science
Image Classification using pretrained ResNets and BiT Models
Hey folks!
Don't forget that tomorrow we have our next webinar "Pachyderm in production: lessons learned"
Our speaker is Oleh Lokshyn is a Machine Learning Architect at SoftServe. He built ML workflows on GCP, Azure, and on-premises for different supervised and unsupervised models. Oleh holds several certifications: Google Cloud Professional Machine Learning Engineer, Google Cloud Professional Data Engineer, Microsoft Certified Azure Data Scientist Associate.
For more info and registration tap 👉🏻 https://bit.ly/3kMUxNF
Don't forget that tomorrow we have our next webinar "Pachyderm in production: lessons learned"
Our speaker is Oleh Lokshyn is a Machine Learning Architect at SoftServe. He built ML workflows on GCP, Azure, and on-premises for different supervised and unsupervised models. Oleh holds several certifications: Google Cloud Professional Machine Learning Engineer, Google Cloud Professional Data Engineer, Microsoft Certified Azure Data Scientist Associate.
For more info and registration tap 👉🏻 https://bit.ly/3kMUxNF
Data Phoenix
Webinar "Pachyderm in production: lessons learned" (RU)
In this talk, we will take a look at yet another MLOps tool - Pachyderm. This tool is gaining in popularity and is unique for some use-cases. The speaker will share the experience of applying Pachyderm to a real-world, BigData NLP project. Most importantly…
📌Dual-Camera Super-Resolution with Aligned Attention Modules
The paper presents a novel approach to reference-based super-resolution with the focus on dual-camera super-resolution, which utilizes reference images for high-quality and high-fidelity results.
https://bit.ly/3um1ubw
The paper presents a novel approach to reference-based super-resolution with the focus on dual-camera super-resolution, which utilizes reference images for high-quality and high-fidelity results.
https://bit.ly/3um1ubw
Are you onboard and receive our weekly newsletter? 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/3A2Qkdj
https://bit.ly/3A2Qkdj
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.
📢 Мы в эфире. Начинаем вебинар "Pachyderm in production: lessons learned", на котором поговорим про MLOps инструмент Pachyderm и его применение в продакшене на примере реального BigData NLP проекта. Присоединяйтесь!
https://bit.ly/3ulEdGI
https://bit.ly/3ulEdGI
💡Recognizing People in Photos Through Private On-Device Machine Learning
Apple's ML research team explains their approach to recognizing people in photos in various poses and wearing extreme accessories by using private, on-device machine learning.
https://apple.co/3zV1OPJ
Apple's ML research team explains their approach to recognizing people in photos in various poses and wearing extreme accessories by using private, on-device machine learning.
https://apple.co/3zV1OPJ
Apple Machine Learning Research
Recognizing People in Photos Through Private On-Device Machine Learning
Photos (on iOS, iPad OS, and Mac OS) is an integral way for people to browse, search, and relive life's moments with their friends…
📌DagsHub — GitHub for Data Science
DagsHub is an open-source DS/ML collaboration platform that allows you to quickly build, scale and deploy ML projects by leveraging the power of git and DVC. Check this one out!
https://bit.ly/2Yj20eR
DagsHub is an open-source DS/ML collaboration platform that allows you to quickly build, scale and deploy ML projects by leveraging the power of git and DVC. Check this one out!
https://bit.ly/2Yj20eR
Medium
DagsHub → Github for Data Science
Data Scientists deserve to browse, preview, share, fork, and merge data & models alongside code.
Hi everyone! Sorry for delay, here's your 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/3kXyNPe
https://bit.ly/3kXyNPe
Data Phoenix
Data Phoenix Digest - ISSUE 25
GPT-4 will have 100 trillion parameters, supercharge image classification with transfer learning, dual-camera super-resolution with aligned attention modules, DagsHub, LightAutoML, TrOCR, FreeStyleGAN, JupyterLab App, cheatsheets, jobs, and more ...
💡Data Science Cheatsheet 2.0
The cheat sheet is based on MIT's Machine Learning courses 6.867 and 15.072. It includes all the info to assist you with exam reviews, interview prep, and anything in-between.
https://bit.ly/2ZGmGxI
The cheat sheet is based on MIT's Machine Learning courses 6.867 and 15.072. It includes all the info to assist you with exam reviews, interview prep, and anything in-between.
https://bit.ly/2ZGmGxI
GitHub
GitHub - aaronwangy/Data-Science-Cheatsheet: A helpful 5-page machine learning cheatsheet to assist with exam reviews, interview…
A helpful 5-page machine learning cheatsheet to assist with exam reviews, interview prep, and anything in-between. - GitHub - aaronwangy/Data-Science-Cheatsheet: A helpful 5-page machine learning c...
Here comes a list of 10 positions available this week, enjoy!
1) Computational Materials Scientist AI / ML – Exabyte.io, San Francisco, Remote
https://bit.ly/3A2VLJ4
2) Senior Python Developer – VITECH, Lviv, Ivano-Frankivsk, Remote
https://bit.ly/3B3aapZ
3) Senior/Middle CV/ML Engineer – Apostera, Odesa, Kyiv, Remote
https://bit.ly/3B3aaX1
4) Junior CV/ML Engineer – Apostera, Odesa, Kyiv, Remote
https://bit.ly/3B3aaX1
5) Senior Machine Learning Engineer (NLP) – Data Science UA, Kyiv, Remote
https://bit.ly/3A3JOmj
For the other 5 positions click 👉🏻 https://bit.ly/3iqnAoS
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!
1) Computational Materials Scientist AI / ML – Exabyte.io, San Francisco, Remote
https://bit.ly/3A2VLJ4
2) Senior Python Developer – VITECH, Lviv, Ivano-Frankivsk, Remote
https://bit.ly/3B3aapZ
3) Senior/Middle CV/ML Engineer – Apostera, Odesa, Kyiv, Remote
https://bit.ly/3B3aaX1
4) Junior CV/ML Engineer – Apostera, Odesa, Kyiv, Remote
https://bit.ly/3B3aaX1
5) Senior Machine Learning Engineer (NLP) – Data Science UA, Kyiv, Remote
https://bit.ly/3A3JOmj
For the other 5 positions click 👉🏻 https://bit.ly/3iqnAoS
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!
📌What’s An OLAP Cube?
An OLAP cube is a multi-dimensional array of data. Online analytical processing (OLAP) is a computer-based technique of analyzing data to look for insights.
https://bit.ly/2YfJZ1h
An OLAP cube is a multi-dimensional array of data. Online analytical processing (OLAP) is a computer-based technique of analyzing data to look for insights.
https://bit.ly/2YfJZ1h
Analytics Engineers Club
What's an OLAP cube? 🎲 - Analytics Engineers Club
Slice, dice, pivot, and hypercubes — we'll cover it all, and along the way learn if this pattern is relevant on a modern data warehouse.
👍1
Hey friends!
What's the best way to start your Monday? Of course, it's to find someone who will inspire you and nurture your desire to move forward! Today, we'd like to introduce you all to Andrew Ng (unless you don't know him already).
Andrew Ng is one of the most recognizable individuals in the Artificial intelligence world. He was a changing force in the AI departments in the world’s two leading technology companies. He's the founder and CEO of Landing AI, founder of deeplearning.ai, general partner at AI Fund, co-founder and chairman at Coursera, and an Adjunct Professor at Stanford University’s Computer Science Department. He was Chief Scientist at Baidu, where he led the company’s AI Group and was responsible for driving the company’s global AI strategy and infrastructure. He was also the founding lead of the Google Brain team.
Andrew Ng is active on LinkedIn. Kindly follow him to stay tuned to his amazing insights and thoughts about AI, ML, DL, and more.
https://bit.ly/2ZP5cPL
What's the best way to start your Monday? Of course, it's to find someone who will inspire you and nurture your desire to move forward! Today, we'd like to introduce you all to Andrew Ng (unless you don't know him already).
Andrew Ng is one of the most recognizable individuals in the Artificial intelligence world. He was a changing force in the AI departments in the world’s two leading technology companies. He's the founder and CEO of Landing AI, founder of deeplearning.ai, general partner at AI Fund, co-founder and chairman at Coursera, and an Adjunct Professor at Stanford University’s Computer Science Department. He was Chief Scientist at Baidu, where he led the company’s AI Group and was responsible for driving the company’s global AI strategy and infrastructure. He was also the founding lead of the Google Brain team.
Andrew Ng is active on LinkedIn. Kindly follow him to stay tuned to his amazing insights and thoughts about AI, ML, DL, and more.
https://bit.ly/2ZP5cPL
💡Robust High-Resolution Video Matting with Temporal Guidance
In this paper, you'll find a robust, real-time, high-resolution human video matting method that achieves new state-of-the-art performance and is much lighter than previous approaches.
https://bit.ly/2Yh5vSX
In this paper, you'll find a robust, real-time, high-resolution human video matting method that achieves new state-of-the-art performance and is much lighter than previous approaches.
https://bit.ly/2Yh5vSX
📌The FP Growth algorithm
In this exploratory post, you'll be guided through a series of steps to apply the FP Growth algorithm in Python, in order to do frequent itemset mining for basket analysis.
https://bit.ly/3Af74xU
In this exploratory post, you'll be guided through a series of steps to apply the FP Growth algorithm in Python, in order to do frequent itemset mining for basket analysis.
https://bit.ly/3Af74xU
Medium
The FP Growth algorithm
Using the FP Growth algorithm in Python to do frequent itemset mining for basket analysis