💡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
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/3FpDDgc
https://bit.ly/3FpDDgc
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.
💡Instance-Conditioned GAN
GANs can generate photo-realistic images. In this paper, the authors use kernel density estimation techniques to introduce a non-parametric approach to modeling distributions of complex datasets.
https://bit.ly/3Ah8yrh
GANs can generate photo-realistic images. In this paper, the authors use kernel density estimation techniques to introduce a non-parametric approach to modeling distributions of complex datasets.
https://bit.ly/3Ah8yrh
📌Apache Spark Monitoring: How To Use Spark API & Open-Source Libraries To Get Better Data Observability Of Your Application
In this guide, you’ll learn how to ensure data observability in Spark using Spark’s internal systems like Listener APIs and Query Execution Listeners, and libraries to track data quality metrics.
https://bit.ly/3oK12D9
In this guide, you’ll learn how to ensure data observability in Spark using Spark’s internal systems like Listener APIs and Query Execution Listeners, and libraries to track data quality metrics.
https://bit.ly/3oK12D9
Databand
Apache Spark Monitoring using Listener APIs and Data quality Libraries
See how to use Listener APIs and data quality libraries to get different levels of data observability for Apache Spark.
With a small delay, we are ready to present our weekly issue of the digest! Later but with high quality😉
And it is already waiting for you on our website! Tap on the link and feel free to subscribe 👇🏻
https://bit.ly/3mA1jpM
P.S. Data Phoenix team appreciates you and thanks to you for being here every week!
And it is already waiting for you on our website! Tap on the link and feel free to subscribe 👇🏻
https://bit.ly/3mA1jpM
P.S. Data Phoenix team appreciates you and thanks to you for being here every week!
Data Phoenix
Data Phoenix Digest - ISSUE 26
New insights into ML, AI, and Data (MAD) landscape, OECD report on investment in AI, China's new take on regulating AI, the FP Growth algorithm, parallelizing Python code, intro to GANs, instance-conditioned GAN, SwinlR, RSDet++, tools, jobs, and more ...
💡Fake It Till You Make It
In this research, the AI/ML team at Microsoft demonstrates that it is possible to perform face-related computer vision in the wild using synthetic data alone.
https://bit.ly/3iMferx
In this research, the AI/ML team at Microsoft demonstrates that it is possible to perform face-related computer vision in the wild using synthetic data alone.
https://bit.ly/3iMferx
⚡️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) Computational Materials Scientist AI / ML - Exabyte.io, San Francisco, Remote
https://bit.ly/3lpZyvR
2) Senior Python Developer - VITECH, Lviv, Ivano-Frankivsk, Remote
https://bit.ly/3iLuCEA
3) Postdoctoral Scholar in HPC and AI Performance - Lawrence Berkeley National Lab, Bay Area, California
https://bit.ly/3aqbmrP
4) Senior Data Scientist - Reddit, New York
https://bit.ly/3uUPs9B
5) Data Scientist, Algorithms - Lyft, San Francisco
https://bit.ly/3amD5tn
For the other 5 positions click 👉🏻 https://bit.ly/30aI3HT
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/3lpZyvR
2) Senior Python Developer - VITECH, Lviv, Ivano-Frankivsk, Remote
https://bit.ly/3iLuCEA
3) Postdoctoral Scholar in HPC and AI Performance - Lawrence Berkeley National Lab, Bay Area, California
https://bit.ly/3aqbmrP
4) Senior Data Scientist - Reddit, New York
https://bit.ly/3uUPs9B
5) Data Scientist, Algorithms - Lyft, San Francisco
https://bit.ly/3amD5tn
For the other 5 positions click 👉🏻 https://bit.ly/30aI3HT
Good morning everyone! Hope you have a great weekend! Here's your dose of positivity as always for this Sunday!🤗
https://bit.ly/2YJtQB8
https://bit.ly/2YJtQB8
Hello everyone! Hope you had a great start of the week! Data Phoenix would like to make your Monday even better and to talk about Bill Schmarzo, one of the top Digital Transformation influencers on Big Data and Data Science. If you don’t follow him yet, kindly check this out!
Bill Schmarzo worked in data warehousing, advanced analytics, and BI niches for over 30 years. As the current CTO, Analytics and IoT for Hitachi Vantara, “The Dean of Big Data” guides the company’s technology strategy and drives “co-creation” efforts with select customers, to leverage IoT and analytics capacity powering digital transformation.
Bill is also famous as a writer. He has published three books: "The Art of Thinking Like a Data Scientist," "Big Data," and "Big Data MBA". Books aside, he is the author of over 300 articles and blog posts on how organizations can become more effective at leveraging data and analytics to power their business models.
https://bit.ly/3FsvwzA
https://bit.ly/3iP2b8U
Bill Schmarzo worked in data warehousing, advanced analytics, and BI niches for over 30 years. As the current CTO, Analytics and IoT for Hitachi Vantara, “The Dean of Big Data” guides the company’s technology strategy and drives “co-creation” efforts with select customers, to leverage IoT and analytics capacity powering digital transformation.
Bill is also famous as a writer. He has published three books: "The Art of Thinking Like a Data Scientist," "Big Data," and "Big Data MBA". Books aside, he is the author of over 300 articles and blog posts on how organizations can become more effective at leveraging data and analytics to power their business models.
https://bit.ly/3FsvwzA
https://bit.ly/3iP2b8U
📌Reinforcement Learning Lecture Series 2021 [DeepMind]
The course offers students 13 lectures on the fundamentals of reinforcement learning and planning in sequential decision problems, as well as more advanced topics and modern deep RL algorithms.
https://bit.ly/3BAEdpl
The course offers students 13 lectures on the fundamentals of reinforcement learning and planning in sequential decision problems, as well as more advanced topics and modern deep RL algorithms.
https://bit.ly/3BAEdpl
📚The-Art-of-Linear-Algebra
The-Art-of-Linear-Algebra is a useful resource that features intuitive visualizations of important concepts introduced in "Linear Algebra for Everyone" by Gilbert Strang. Available as a PDF file.
https://bit.ly/3BCr4w3
The-Art-of-Linear-Algebra is a useful resource that features intuitive visualizations of important concepts introduced in "Linear Algebra for Everyone" by Gilbert Strang. Available as a PDF file.
https://bit.ly/3BCr4w3
GitHub
GitHub - kenjihiranabe/The-Art-of-Linear-Algebra: Graphic notes on Gilbert Strang's "Linear Algebra for Everyone"
Graphic notes on Gilbert Strang's "Linear Algebra for Everyone" - GitHub - kenjihiranabe/The-Art-of-Linear-Algebra: Graphic notes on Gilbert Strang's "Lin...
Hello everyone! 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/3v7cHNG
https://bit.ly/3v7cHNG
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.