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Making AI Work with Small Data | IndustryWeek
# Synthetic data generation
## GANs, variational autoencoders, domain randomization and data augmentation can be used to do this
# Transfer learning
# Self-supervised learning
# few-shot learning
## reformulating problem to help the AI system to learn an easier, less data hungry inspection task while achieving the same goal
One-shot learning
# anomaly detection
## flag anything that deviates significantly from the OK images as a potential problem.
# Hand-coded knowledge
# Human-in-the-loop
## AI shows something to a human expert and defers to their judgement when not sure
big  small  data  ai  artificial  intelligence  machine  learning  challenge  challenges  lack  of  problem  with 
16 days ago by yencarnacion
3 Powerful Uses of Machine Learning in Marketing
Uncovering trends 
Targeting the right influencers
Analyzing campaigns
ai  artificial  intelligence  machine  learning  use  uses  case  cases  marketing  entrepreneur  magazine  article 
august 2019 by yencarnacion
yencarnacion/google-research: Google AI Research
Training Data:
# Prostate
https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga
# breast
https://camelyon16.grand-challenge.org/
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The Camelyon16 dataset utilized to develop the deep learning algorithms used in this study is available from the Camelyon challenge8 (https://camelyon16.grand-challenge.org/). The prostate dataset from TCGA that was used to develop the deep learning algorithms used in this study is available from the Genomic Data Commons portal (https://portal.gdc.cancer.gov/), which is based on data generated by the TCGA Research Network (http://cancergenome.nih.gov/).
---
https://doi.org/10.1038/s41591-019-0539-7
github  google  cancer  research  open  source  ai  artificial  intelligence  ml  machine  deep  learning  pdf  paper  microscope  ar  augmented  reality 
august 2019 by yencarnacion
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