Do no harm: a roadmap for responsible machine learning for health care
https://www.nature.com/articles/s41591-019-0548-6

Deep Learning Pioneer Yoshua Bengio Says AI Is Not Magic And Intel AI Experts Explain Why And How

https://www.forbes.com/sites/gilpress/2019/09/20/deep-learning-pioneer-yoshua-bengio-says-ai-is-not-magic-and-intel-ai-experts-explain-why-and-how/#19bb57b712a6

Large e-retailer image dataset for visual search and product classification. https://arxiv.org/abs/1909.08612

The Disruptions of 5G on Data-driven Technologies and Applications. https://arxiv.org/abs/1909.08096

Adversarial Attacks and Defenses in Images, Graphs and Text: A Review. https://arxiv.org/abs/1909.08072

Megatron-LM: Training Multi-Billion Parameter Language Models Using GPU Model Parallelism. https://arxiv.org/abs/1909.08053

A Deep Learning Approach to Data Compression
Blog by Friso Kingma : https://bair.berkeley.edu/blog/2019/09/19/bit-swap/
#ArtificialIntelligence #DeepLearning #MachineLearning

We're thrilled to announce that the Fall 2020 admissions applications are open! We're ready for the next cohort of future Data Scientists! Please click on the links below for more information! The application deadline for the MS Degree is January 22, 2020 and the deadline for the Ph.D. is December 12, 2019.

For MS Degree information please click the link below.:
https://cds.nyu.edu/ms-adm-req/

For Ph.D. information please click the link below:
https://cds.nyu.edu/academics/phd/

ns3-gym: Extending OpenAI Gym for Networking Research
Piotr Gawłowicz and Anatolij Zubow : https://arxiv.org/abs/1810.03943
#OpenAIGym #Networking #Research

Here's a list of 7 top research on arXiV on AI/deep learning for August 2019 as per Daniel Gutierrez

1) A Probabilistic Representation of Deep Learning

Link: https://arxiv.org/pdf/1908.09772v1.pdf

2) Inception-inspired LSTM for Next-frame Video Prediction
@ArtificialIntelligenceArticles
Link: https://arxiv.org/pdf/1909.05622.pdf

3) Systematic Analysis of Image Generation using GANs

Link: https://arxiv.org/ftp/arxiv/papers/1908/1908.11863.pdf
@ArtificialIntelligenceArticles
4) Dynamic Stale Synchronous Parallel Distributed Training for Deep Learning

Link: https://arxiv.org/pdf/1908.11848.pdf

5) Discovering Reliable Correlations in Categorical Data

Link: https://arxiv.org/pdf/1908.11682.pdf

6) Smaller Models, Better Generalization

Link: https://arxiv.org/pdf/1908.11250.pdf

7) An Auto-ML Framework Based on GBDT for Lifelong Learning

Link: https://arxiv.org/pdf/1908.11033.pdf

Source: https://insidebigdata.com/2019/09/18/best-of-arxiv-org-for-ai-machine-learning-and-deep-learning-august-2019/


@ArtificialIntelligenceArticles

Best Practices for Picking a Machine Learning Model
https://www.kaggle.com/lavanyashukla01/picking-the-best-model-a-whirlwind-tour-of-model

A Friendly Introduction to Real-Time Object Detection using the Powerful SlimYOLOv3 Framework
https://www.analyticsvidhya.com/blog/2019/08/introduction-slimyolov3-real-time-object-detection/

Senior Data Scientist – Digital
https://ai-jobs.net/job/senior-data-scientist-digital/

Metropolis Colorized with DeOldify https://www.youtube.com/watch?v=t75yctjjfx0

CS221: Artificial Intelligence: Principles and Techniques
https://web.stanford.edu/class/cs221/


https://youtu.be/OQQ-W_63UgQ?fbclid=IwAR2ig2e9oqHPwem0S_6FtLky7QRxIO3BBYyRdyFvHUmukV0cCuKnSDImzsg

Deep Multi-Agent Reinforcement Learning

Jakob N. Foerster : https://ora.ox.ac.uk/objects/uuid:a55621b3-53c0-4e1b-ad1c-92438b57ffa4