The right AI Tools for a Happy Data Scientist

The right AI Tools for a Happy Data Scientist

--

From our proprietary AI framework to our Data Platform, the key-enabler for scalability, deep dive into Earthcube's tools to build sky-rocketing deep learning models.

--
CREDIT

Speaker - Julie Imbert
With the apparition of the Earthcube team
Script - Julie Imbert & Ségolène Husson
With the participation of Arnaud, Renaud and all the Earthcube team
Filmmaker, editing & motion design - Julien Mascheroni

ILLUSTRATIONS
Earthcube proprietary code and detections
Earthcube platform screenshots
Satellite Images
fMoW dataset, Functional Map of the World, CVPR, Gordon Christie, Neil Fendley, James Wilson, and Ryan Mukherjee, 2018
Maxar

Articles
Yarin Gal, Riashat Islam, Zoubin Ghahramani, Deep Bayesian Active Learning with Image Data, 2017, arXiv,
Sanghyun Woo, Jongchan Park, Joon-Young Lee, In So Kweon, CBAM: Convolutional Block Attention Module, 2018, arXiv,
Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger, Snapshot Ensembles: Train 1, get M for free, 2017, arXiv,
James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A. Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, Raia Hadsell, Overcoming catastrophic forgetting in neural networks, 2016, arXiv,
Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin, Dmitry Vetrov, Andrew Gordon Wilson, Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs, 2018, arXiv,
Tsung-Yi Lin, Priya Goyal, Ross B. Girshick, Kaiming He, Piotr Dollár, Focal Loss for Dense Object Detection, 2017, arXiv,
Olaf Ronneberger, Philipp Fischer, Thomas Brox, U-Net: Convolutional Networks for Biomedical Image Segmentation, 2015, arXiv,
Vijay Badrinarayanan, Alex Kendall, Roberto Cipolla, SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation, 2015, arXiv,
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun, Deep Residual Learning for Image Recognition, 2015, arXiv,
Rodney LaLonde, Ulas Bagci, Capsules for Object Segmentation, 2018, arXiv,
Kaiming He, Georgia Gkioxari, Piotr Dollár, Ross B. Girshick, Mask R-CNN, 2017, arXiv,
Shaoqing Ren, Kaiming He, Ross B. Girshick, Jian Sun, Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, 2015,arXiv,
Karen Simonyan and Andrew Zisserman, Very Deep Convolutional Networks for Large-Scale Image Recognition, 2014, arXiv,
Joseph Redmon, Ali Farhadi, YOLOv3: An Incremental Improvement, 2018, arXiv,
Sara Sabour, Nicholas Frosst, Geoffrey E. Hinton, Dynamic Routing Between Capsules, 2017, arXiv,
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia, Pyramid Scene Parsing Network, 2016, arXiv,
Chao Peng, Xiangyu Zhang, Gang Yu, Guiming Luo, Jian Sun, Large Kernel Matters - Improve Semantic Segmentation by Global Convolutional Network, 2017, arXiv,
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun, Identity Mappings in Deep Residual Networks, 2016, arXiv,
Saining Xie, Ross B. Girshick, Piotr Dollár, Zhuowen Tu, Kaiming He, Aggregated Residual Transformations for Deep Neural Networks, 2016, arXiv,
Abhijit Guha Roy, Nassir Navab, Christian Wachinger, Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks, 2018, arXiv,
Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson, Averaging Weights Leads to Wider Optima and Better Generalization, 2018, arXiv.
Murat Seckin Ayhan, Philipp Berens, Test-time data augmentation for estimation of heteroscedastic aleatoric uncertainty in deep neural networks, 2018,
Yarin Gal, Zoubin Ghahramani, Dropout as a bayesian approximation: Representing model uncertainty in deep learning, 2015.

--

https://www.earthcube.eu
https://www.youtube.com/playlist?list=PLCqfmZWS97Q6QEJlF9zi2jzb7OIWN-eHz
https://medium.com/earthcube-stories

Видео The right AI Tools for a Happy Data Scientist канала Preligens