📌Geometric Deep Learning [Course]

GDL is a free course that closely follows the contents of GDL proto-book by Michael M. Bronstein, Joan Bruna, Taco Cohen, and Petar Veličković. All materials and artefacts are publicly available.
https://bit.ly/3FRpDvW

Hello friends! Data Phoenix team would like to make an announcement. Now, we'll release our weekly digest on Friday. We believe that it'll give you more time to check it out, and we'll be able to provide even more high-quality content to you. Hope you aren't against the change and will love what we have in store for you. So, see you a bit later today!
https://bit.ly/3vsFQmR

Hey friends! Data Phoenix is here and we want to tell you that 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/3DLEKW8

​​⚡️Hello friends! How is your weekend going?
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) Computational Materials Scientist AI / ML - Exabyte.io, San Francisco, Remote
https://bit.ly/3p5mpiE
2) Data Scientist Demand - TripAdvisor, Paris, France
https://bit.ly/2YOnikx
3) Marketing Data Scientist - Intercom, Dublin, Ireland
https://bit.ly/3mYJy3J
4) Data Scientist II - AWS, Seattle, Washington
https://bit.ly/3mYJyAL
5) Sr Data Scientist, Machine Learning - Coursera, Canada (Remote)
https://bit.ly/3lLp4fa

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!

​​Good morning! Hope you have a great weekend! Here's your dose of positivity as always for this Sunday!🤗
https://bit.ly/3pazd7i

📌The Human Regression Ensemble

In this article, Justin Domke plays with the idea that humans can do predictions as well as algorithms for simple tasks. Let's check out what's come out of it!
https://bit.ly/3DLIjvq

​​⚡️Hey guys! We'd like to start this Monday with a story of Carla Gentry - a Data Scientist and founder of Analytical-Solution.

She is a great example of a strong woman (and we do love that!). Being a single mother of two sons was a challenge, but despite all the circumstances, she was eager to learn and grow. She worked in the Developmental Math Lab her entire tenure with UTC, assisting students with all levels of mathematics. After graduating from UTC with a double major in Applied Mathematics and Economics in 1998, she moved to the Chicago area to start her career in analytics.

During the last 19+ years, she has worked for such companies as Discover Financial Services, J&J, Hershey, Kraft, Kellogg’s, SCJ, McNeil, and Firestone. She says that being called a data nerd is a badge of courage for this curious Mathematician/Economist because knowledge is power and companies are now acknowledging its importance.
https://bit.ly/3AQbKL4

💡ResNet Strikes Back: An Improved Training Procedure in timm

In this paper, the authors re-evaluate the performance of advanced ResNet-50 and share competitive training settings and pre-trained models in the timm open-source library.
https://bit.ly/3vkIpHk

📌DVC Alternatives For Experiment Tracking

In this article, the Neptune team explore the experiment tracking tool called Data Version Control (DVC), and also compares and reviews its alternatives to find the best solution available.
https://bit.ly/3vxyVc0

💡Simple Recurrent Neural Networks Is All We Need for Clinical Events Predictions Using EHR Data

The authors conduct a thorough benchmark of RNN architectures in modeling EHR data on two prediction tasks: developing heart failure and early readmission for inpatient hospitalization.

https://bit.ly/3phxIEm

To create a powerful ML you need well-organized data, this is how it works. If you want to know more meet Dr. Zech and Dr. Bazhirov on October 22nd to learn more about facilitating data science, for materials and chemicals through catecom - an open-source collaborative approach to the categorization of computational models including data structures, database schemas, and their applications.

The webinar focuses on helping users execute computational materials science tasks on Exabyte.io and introduces an approach capable of representing complex model structures in a data-centric manner suitable for the applications of AI/ML.

Register at https://bit.ly/3B3vudX

📌Understanding Simple Recurrent Neural Networks In Keras

In this tutorial, you'll learn about the structure of RNN, how RNN computes the output when given an input, how to prepare data for a SimpleRNN in Keras, and how to train a SimpleRNN model.

https://bit.ly/30M0ovb

Hi friends! Don't forget 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/3vx56Is

💡Keypoint Communities

In this paper, Duncan Zauss et al. present a fast bottom-up method that jointly detects over 100 keypoints on humans or objects, also referred to as human/object pose estimation.
https://bit.ly/3nc2XOC

Hello friends!
Great news! Data Phoenix just published the latest 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/3m6y3Ii

🎥Graph Neural Network for Lagrangian Simulation

The video explains how you can design, build, and use GNNs for Langrarian simulation. Based on the work presented at American Physical Society - Division of Fluid Dynamics Annual Meeting.

https://bit.ly/3b0Yhph

​​⚡️Hello guys! How is your weekend going?⚡️
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 Product Manager - FreshBooks, Canada (Remote)
https://bit.ly/3Eca14S
2) Machine Learning Engineer - Domino Data Lab, Europe (Remote)
https://bit.ly/2Zhkkp2
3) Senior Data Scientist - Heap, Remote
https://bit.ly/3Gcy4lL
4) Machine Learning Engineer - Wikimedia Foundation, Remote
https://bit.ly/3nj9irD
5) Principal Data Scientist - Twilio, US (Remote)
https://bit.ly/3B8S84E

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!

​​Good morning friends! Here's your dose of positivity for this Sunday!🤗
https://bit.ly/2ZgDCdU

💡MLOps Model Stores: Definition, Functionality, Tools Review

Is there a way to keep all the collaboration on developing and deploying ML models efficient and streamlined? The team at Neptune seems to have found the right answer!
https://bit.ly/3b5zAYB
https://bit.ly/3b5zAYB)

​​Hello everyone! Today, we'd like to introduce you to Chris Messina. A living legend who has spent over 15 years on the edge of social technology.

Chris's in charge of the West Coast business development for Republic, an inclusive fundraising platform disrupting conventional venture capital. He often plays product therapist and helps founders and makers nail their launches on Product Hunt.

He's best known for inventing the hashtag, but he has also designed products and experiences for Google and Uber, founded startups, and changed the world with such social innovations as co-working and BarCamp. Being a world-known product designer, he has spoken about social tech, product design, synthetic media and founder culture at TEDx, SXSW, Google I/O, Microsoft’s Future Decoded, and many other leading conferences.

He also appeared (briefly!) in The Social Dilemma on Netflix and was featured in at least two books: No Filte by Sarah Frier, and Billion Dollar Loser by Reeves Wiedeman.
https://bit.ly/3jzBQvN

📌Adding Data to Build a More Generic Model
When you want to change datasets and start tracking how they affect the model, use DVC remote. You'll be able to upload/download GBs of data and see how changes affect individual experiments.
https://bit.ly/3Gg6PXL