Anthill Inside 2017
On theory and concepts in Machine Learning, Deep Learning and Artificial Intelligence. Formerly Deep Learning Conf.
PyTorch demystified: why did I switch?
Sherin Thomas, CoWrks
32 minutes29 July 2017
Apache MXNet: a highly memory efficient deep learning framework.
Girish Patil, AWS
20 minutes29 July 2017
Saving the Princess with Deep Learning.
Navin Pai, IIIT-B
18 minutes29 July 2017
How deep is Deep Learning?
Amar Lalwani, Funtoot
34 minutes29 July 2017
Synthetic gradients: decoupling layers of neural nets.
Anuj Gupta, Freshdesk
41 minutes29 July 2017
Keep calm and trust your model: on explainability of ML models.
Praveen Sridhar, DataLog.ai
30 minutes29 July 2017
Adversarial attacks on Deep Learning models.
Konda Reddy Mopuri, IISc
44 minutes29 July 2017
Sponsored keynote: "AI: unleashing the next wave."
Milind Hanchinmani, Intel
30 minutes29 July 2017
Identifying urban makeshift communities using satellite imagery and geo-coded data.
Akarsh Zingade, DataKind
22 minutes29 July 2017
Hitchhiker’s guide to Generative Adversarial Networks (GANs).
Ramanan Balakrishnan, Semantics3
43 minutes29 July 2017
Unsupervised and semi-supervised Deep Learning for medical imaging.
Kiran Vaidhya, Predible Health
33 minutes29 July 2017
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Anthill Inside is a forum for conversations about risk mitigation and governance in Artificial Intelligence and Deep Learning. AI developers, researchers, startup founders, ethicists, and AI enthusiasts are encouraged to:
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