Forwarded from Data Science Boom
Deepmind teaches AI to follow navigational directions like humans
http://bit.ly/2NXtOMc
You created a machine learning application. Now make sure it’s secure.
https://oreil.ly/2O0yIZ9
A Conversation about Tech Ethics with the New York Times Chief Data Scientist
http://bit.ly/2NZBmxZ
Tutorial: Poisson Regression in R
http://bit.ly/2F7QOFv
A Data-Driven Tribute to Captain Marvel
https://tabsoft.co/2F7pl76
http://bit.ly/2NXtOMc
You created a machine learning application. Now make sure it’s secure.
https://oreil.ly/2O0yIZ9
A Conversation about Tech Ethics with the New York Times Chief Data Scientist
http://bit.ly/2NZBmxZ
Tutorial: Poisson Regression in R
http://bit.ly/2F7QOFv
A Data-Driven Tribute to Captain Marvel
https://tabsoft.co/2F7pl76
Forwarded from Data Science Boom
AI Interprets What Rodents Are Saying
http://bit.ly/2O44Mes
LazyNLP for Creating Massive Text Datasets
http://bit.ly/2O3aKfN
How Artificial Intelligence Is Changing Science
http://bit.ly/2FcetF2
3 Levels of Deep Learning Competence
http://bit.ly/2O4MeuJ
How many high school stars make it in the NBA?
http://bit.ly/2FdHlww
http://bit.ly/2O44Mes
LazyNLP for Creating Massive Text Datasets
http://bit.ly/2O3aKfN
How Artificial Intelligence Is Changing Science
http://bit.ly/2FcetF2
3 Levels of Deep Learning Competence
http://bit.ly/2O4MeuJ
How many high school stars make it in the NBA?
http://bit.ly/2FdHlww
Forwarded from Data Science Boom
Boom! What to read on the weekend, Issue #54
The Most Complete List of Best AI Cheat Sheets
http://bit.ly/2O4O1Qg
The case for building expertise to work on US AI policy, and how to do it
http://bit.ly/2O7GgsZ
Advanced Machine Learning with Basic Excel
http://bit.ly/2O4O6Dy
Natural Language Processing in Pharma – Current Applications
http://bit.ly/2FhRacP
Harnessing Organizational Knowledge for Machine Learning
http://bit.ly/2O9M4Cb
A Day in the Life: Women and Men
http://bit.ly/2O5sKGn
TF-Replicator: Distributed Machine Learning for Researchers
http://bit.ly/2Fe9Vha
Round the World with Nellie Bly
https://tabsoft.co/2FiBt5j
The full moon calendar 1900-2050. 150 years of data in an overview
http://bit.ly/2ObpLMI
Worldwide mobile data pricing: The cost of 1GB of mobile data in 230 countries
http://bit.ly/2Ffhp3N
The Most Complete List of Best AI Cheat Sheets
http://bit.ly/2O4O1Qg
The case for building expertise to work on US AI policy, and how to do it
http://bit.ly/2O7GgsZ
Advanced Machine Learning with Basic Excel
http://bit.ly/2O4O6Dy
Natural Language Processing in Pharma – Current Applications
http://bit.ly/2FhRacP
Harnessing Organizational Knowledge for Machine Learning
http://bit.ly/2O9M4Cb
A Day in the Life: Women and Men
http://bit.ly/2O5sKGn
TF-Replicator: Distributed Machine Learning for Researchers
http://bit.ly/2Fe9Vha
Round the World with Nellie Bly
https://tabsoft.co/2FiBt5j
The full moon calendar 1900-2050. 150 years of data in an overview
http://bit.ly/2ObpLMI
Worldwide mobile data pricing: The cost of 1GB of mobile data in 230 countries
http://bit.ly/2Ffhp3N
Forwarded from Crypto Investment
The blockchain project SingularityNET on Thursday announced the start of cooperation with one of the largest insurance corporations in the world, Ping An.
“Ping An Technology and SingularityNET have agreed to cooperate in the field of artificial intelligence, and are also considering the possibility of launching other joint initiatives related, in particular, with optical character recognition technology (OCR) and machine learning,” said Ping An Bai, head of the AI-direction. Meng.
As the project explains in his blog, initially his collaboration with Ping An will focus on three main areas: OCR, Cross Validation and machine learning, "where the SingularityNET environmental system can find commercial applications."
In the future, the scope of the agreement may be expanded, SingularityNET claims, pointing to insurance company initiatives such as Ping An Smart City and One Minute Clinic, which uses artificial intelligence technology.
The SingularityNET project raised $ 32.8 million through ICO at the end of 2017, and its AGI token showed positive dynamics regarding Bitcoin and Ethereum after entering the market but lost half of its value in dollar terms.
Ping An was founded in 1988 and is included in the Hang Seng Index, calculated as the weighted average of the largest capitalized shares of 50 Hong Kong stock companies, which make up 58% of the capitalization of the Hong Kong Stock Exchange. In 2018, according to one of the versions, Ping An was recognized as the third most expensive financial services company in the world.
“Ping An Technology and SingularityNET have agreed to cooperate in the field of artificial intelligence, and are also considering the possibility of launching other joint initiatives related, in particular, with optical character recognition technology (OCR) and machine learning,” said Ping An Bai, head of the AI-direction. Meng.
As the project explains in his blog, initially his collaboration with Ping An will focus on three main areas: OCR, Cross Validation and machine learning, "where the SingularityNET environmental system can find commercial applications."
In the future, the scope of the agreement may be expanded, SingularityNET claims, pointing to insurance company initiatives such as Ping An Smart City and One Minute Clinic, which uses artificial intelligence technology.
The SingularityNET project raised $ 32.8 million through ICO at the end of 2017, and its AGI token showed positive dynamics regarding Bitcoin and Ethereum after entering the market but lost half of its value in dollar terms.
Ping An was founded in 1988 and is included in the Hang Seng Index, calculated as the weighted average of the largest capitalized shares of 50 Hong Kong stock companies, which make up 58% of the capitalization of the Hong Kong Stock Exchange. In 2018, according to one of the versions, Ping An was recognized as the third most expensive financial services company in the world.
Forwarded from Data Science Boom
Boom! Weekly selection from DSB. Issue #45
The TOP 10 most popular links for the week
1. The best of ML. 40 of the best resources for Machine Learning
http://bit.ly/2NS1Z8h
2. A new tool from Google and OpenAI lets us better see through the eyes of artificial intelligence
http://bit.ly/2NYtInO
3. Artificial Intelligence at NASA – Current Projects and Applications
http://bit.ly/2NWP2Kk
4. Visual Vocabulary
http://bit.ly/2Fau0VM
5. Natural Language Processing Tutorial for Deep Learning Researchers
http://bit.ly/2Fa709q
6. Machine Learning for Beginners: An Introduction to Neural Networks
http://bit.ly/2NTbwvC
7. The A.I. Diet. Forget government-issued food pyramids. Let an algorithm tell you how to eat.
https://nyti.ms/2F99dBN
8. The Most Complete List of Best AI Cheat Sheets
http://bit.ly/2O4O1Qg
9. 3 Levels of Deep Learning Competence
http://bit.ly/2O4MeuJ
10. LazyNLP for Creating Massive Text Datasets
http://bit.ly/2O3aKfN
The TOP 10 most popular links for the week
1. The best of ML. 40 of the best resources for Machine Learning
http://bit.ly/2NS1Z8h
2. A new tool from Google and OpenAI lets us better see through the eyes of artificial intelligence
http://bit.ly/2NYtInO
3. Artificial Intelligence at NASA – Current Projects and Applications
http://bit.ly/2NWP2Kk
4. Visual Vocabulary
http://bit.ly/2Fau0VM
5. Natural Language Processing Tutorial for Deep Learning Researchers
http://bit.ly/2Fa709q
6. Machine Learning for Beginners: An Introduction to Neural Networks
http://bit.ly/2NTbwvC
7. The A.I. Diet. Forget government-issued food pyramids. Let an algorithm tell you how to eat.
https://nyti.ms/2F99dBN
8. The Most Complete List of Best AI Cheat Sheets
http://bit.ly/2O4O1Qg
9. 3 Levels of Deep Learning Competence
http://bit.ly/2O4MeuJ
10. LazyNLP for Creating Massive Text Datasets
http://bit.ly/2O3aKfN
Forwarded from Automatics & Robotics & Arduino
Adafruit IO Environmental Monitor for Feather or Raspberry Pi
Build an internet-enabled environmental monitor to see what's in th
Knowing what's in the air you breathe is important - and building an environmental monitor is a way to visualize the invisible properties of the air you inhale.
This guide covers building a small, internet-enabled environmental monitor which can track a range of data such from temperature to UV-level to the amount of total-volatile-organic-compounds present in the air.
https://learn.adafruit.com/adafruit-io-air-quality-monitor/overview
Build an internet-enabled environmental monitor to see what's in th
Knowing what's in the air you breathe is important - and building an environmental monitor is a way to visualize the invisible properties of the air you inhale.
This guide covers building a small, internet-enabled environmental monitor which can track a range of data such from temperature to UV-level to the amount of total-volatile-organic-compounds present in the air.
https://learn.adafruit.com/adafruit-io-air-quality-monitor/overview
Adafruit Learning System
Adafruit IO Environmental Monitor for Feather or Raspberry Pi
Build an internet-enabled environmental monitor to see what's in the air you breathe using Arduino or CircuitPython
Forwarded from Data Science Boom
We’re training AI to keep an eye on government. Come join us.
http://bit.ly/2OceJ9Y
World Health Organisation: Global Suicide Trends & Analysis
http://bit.ly/2O9hlW2
TwoTone. A free web app to turn data into sound and music
http://bit.ly/2FiLxeg
ML for Everyone. In simple words. With real-world examples. Yes, again
http://bit.ly/2FiBLcb
A colorful π chart
http://bit.ly/2OdVYmA
http://bit.ly/2OceJ9Y
World Health Organisation: Global Suicide Trends & Analysis
http://bit.ly/2O9hlW2
TwoTone. A free web app to turn data into sound and music
http://bit.ly/2FiLxeg
ML for Everyone. In simple words. With real-world examples. Yes, again
http://bit.ly/2FiBLcb
A colorful π chart
http://bit.ly/2OdVYmA
Forwarded from Data Science Boom
China is about to overtake America in AI research
http://bit.ly/2OdWn8A
People think that data is in the cloud, but it’s not. It’s in the ocean.
https://nyti.ms/2OaOhgX
10 things R can do that might surprise you
http://bit.ly/2Oap7yR
Model Zoo. Discover open source deep learning code and pretrained models.
http://bit.ly/2ObZMo2
How People Meet Their Partners
http://bit.ly/2O7y2Rw
http://bit.ly/2OdWn8A
People think that data is in the cloud, but it’s not. It’s in the ocean.
https://nyti.ms/2OaOhgX
10 things R can do that might surprise you
http://bit.ly/2Oap7yR
Model Zoo. Discover open source deep learning code and pretrained models.
http://bit.ly/2ObZMo2
How People Meet Their Partners
http://bit.ly/2O7y2Rw
Forwarded from Data Science by ODS.ai 🦜
Another major release of #SpaCy
👽 ULMFit/BERT/ELMo-like language model pretraining
📐 Better matching & rule-based NER
🧮 Platform-independent matrix multiplication
🚀 2-3 times faster tokenization
⏳ Installation without local compilers
Link: https://explosion.ai/blog/spacy-v2-1
#NLP #python
👽 ULMFit/BERT/ELMo-like language model pretraining
📐 Better matching & rule-based NER
🧮 Platform-independent matrix multiplication
🚀 2-3 times faster tokenization
⏳ Installation without local compilers
Link: https://explosion.ai/blog/spacy-v2-1
#NLP #python
Explosion
Introducing spaCy v2.1 · Explosion
Version 2.1 of the spaCy Natural Language Processing library includes a huge number of features, improvements and bug fixes. In this post, we highlight some of the things we're especially pleased with, and explain some of the most challenging parts of preparing…
Forwarded from Data Science Boom
This resume does not exist
http://bit.ly/2O8cN2d
Here’s How We’ll Know an AI Is Conscious
http://bit.ly/2O9f2Cc
A Step-by-Step NLP Guide to Learn ELMo for Extracting Features from Text
http://bit.ly/2Ob9QO4
FastCharts to make charts fast
http://bit.ly/2Fk4mhn
When were CDs, cassettes, and other recording formats most profitable?
https://tabsoft.co/2O9x3QL
http://bit.ly/2O8cN2d
Here’s How We’ll Know an AI Is Conscious
http://bit.ly/2O9f2Cc
A Step-by-Step NLP Guide to Learn ELMo for Extracting Features from Text
http://bit.ly/2Ob9QO4
FastCharts to make charts fast
http://bit.ly/2Fk4mhn
When were CDs, cassettes, and other recording formats most profitable?
https://tabsoft.co/2O9x3QL
Forwarded from Data Science by ODS.ai 🦜
Neural network that turns sketches into realistic photo.
Paper is called «Semantic Image Synthesis with Spatially-Adaptive Normalization».
#CVPR19 oral paper on a new conditional normalization layer for semantic image synthesis #SPADE and its demo app #GauGAN
ArXiV: https://arxiv.org/abs/1903.07291
Website: https://nvlabs.github.io/SPADE/
#GAN #CV #DL
Paper is called «Semantic Image Synthesis with Spatially-Adaptive Normalization».
#CVPR19 oral paper on a new conditional normalization layer for semantic image synthesis #SPADE and its demo app #GauGAN
ArXiV: https://arxiv.org/abs/1903.07291
Website: https://nvlabs.github.io/SPADE/
#GAN #CV #DL
Forwarded from Computer Science and Programming
Discover open source Deep Learning code and pretrained models.
Deep learning researchers easily find pre-trained models for a variety of platforms and uses. Great resource
Deep learning researchers easily find pre-trained models for a variety of platforms and uses. Great resource
Forwarded from Computer Science and Programming
Forwarded from Data Science Boom
Facebook AI researchers create a text-based adventure to study how AI speak and act
http://bit.ly/2FiErXr
The B2B analytics playbook: Capturing unrealized potential in telcos
https://mck.co/2FiEMtb
The Promise of Hierarchical Reinforcement Learning
http://bit.ly/2O8do3X
Radical Change Is Coming To Data Science Jobs
http://bit.ly/2ObskOH
8 Books for Getting Started With Computer Vision
http://bit.ly/2O9O4KJ
http://bit.ly/2FiErXr
The B2B analytics playbook: Capturing unrealized potential in telcos
https://mck.co/2FiEMtb
The Promise of Hierarchical Reinforcement Learning
http://bit.ly/2O8do3X
Radical Change Is Coming To Data Science Jobs
http://bit.ly/2ObskOH
8 Books for Getting Started With Computer Vision
http://bit.ly/2O9O4KJ
Forwarded from Data Science by ODS.ai 🦜
Next-level learning approach: using MRI to peek into baby brains to improve CV
MRI Scanning 17 babies for 26 hours to see how face-recognizing brain regions mature. When just 4-6 months, babies prefer to look at faces & socially relevant things. This means face recognition is learned via evolution: data-hungry & sample-inefficient.
Link: https://www.nature.com/articles/ncomms13995
#nature
MRI Scanning 17 babies for 26 hours to see how face-recognizing brain regions mature. When just 4-6 months, babies prefer to look at faces & socially relevant things. This means face recognition is learned via evolution: data-hungry & sample-inefficient.
Link: https://www.nature.com/articles/ncomms13995
#nature
Nature
Organization of high-level visual cortex in human infants
Nature Communications - Adult visual cortex is organized into regions that respond to categories such as faces and scenes, but it is unclear if this depends on experience. Here, authors measured...
Forwarded from Data Science by ODS.ai 🦜
One-shot object detection
Long and complete post explaining how these one-shot detectors work and how they are trained and evaluated.
Link: https://machinethink.net/blog/object-detection/
#cv #dl #objectdetection
Long and complete post explaining how these one-shot detectors work and how they are trained and evaluated.
Link: https://machinethink.net/blog/object-detection/
#cv #dl #objectdetection
Forwarded from Data Science by ODS.ai 🦜
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
A deep convolutional neural network for breast cancer screening exam classification, trained and evaluated on over 200,000 exams (over 1,000,000 images). #nn achieves an #AUC of 0.895 in predicting whether there is a cancer in the breast, when tested on the screening population.
Link: https://arxiv.org/abs/1903.08297
#cv #dl #cancer #objectdetection
A deep convolutional neural network for breast cancer screening exam classification, trained and evaluated on over 200,000 exams (over 1,000,000 images). #nn achieves an #AUC of 0.895 in predicting whether there is a cancer in the breast, when tested on the screening population.
Link: https://arxiv.org/abs/1903.08297
#cv #dl #cancer #objectdetection
arXiv.org
Deep Neural Networks Improve Radiologists' Performance in...
We present a deep convolutional neural network for breast cancer screening exam classification, trained and evaluated on over 200,000 exams (over 1,000,000 images). Our network achieves an AUC of...