uergen Schmidhuber: Critique of Turing Award for Drs. Bengio & Hinton & LeCun
@ArtificialIntelligenceArticles

https://people.idsia.ch/~juergen/critique-turing-award-bengio-hinton-lecun.html


@ArtificialIntelligenceArticles

AI Paper Summary Video
Paper: BERT: Pre-training of Deep Bidirectional Transformers forLanguage Understanding
Link: https://arxiv.org/pdf/1810.04805.pdf
Video Summary: https://youtu.be/M4rq1Ce6wyM
Summary by Dhruvil Karani (Data Scientist)
B.Eng. (IIT Guwahati)

On the Measure of Intelligence by François Chollet - Part 4: The ARC Challenge (Paper Explained)
https://www.youtube.com/watch?v=O9kFX33nUcU

To help practitioners keep fairness considerations at the forefront of their minds, Google’s engineering education and ML fairness teams developed a 60-minute self-study training module on fairness. https://www.blog.google/technology/ai/new-course-teach-people-about-fairness-machine-learning/

ICYMI: A browser extension that automatically finds code implementations for machine learning papers anywhere on the web (Google, Arxiv, Twitter, Scholar, and other sites)!
@ArtificialIntelligenceArticles
https://chrome.google.com/webstore/detail/mlai-code-implementation/aikkeehnlfpamidigaffhfmgbkdeheil

https://addons.mozilla.org/en-US/firefox/addon/code-finder-catalyzex/

@ArtificialIntelligenceArticles

Deep Learning with Keras Series By Ali Masri
1. Deep Learning with Keras Tutorial https://www.marktechpost.com/2019/06/11/deep-learning-with-keras-tutorial-part-1/
2. Data Pre-processing for Deep Learning models https://www.marktechpost.com/2019/06/14/data-pre-processing-for-deep-learning-models-deep-learning-with-keras-part-2/
3. Regression with Keras https://www.marktechpost.com/2019/06/17/regression-with-keras-deep-learning-with-keras-part-3/
4. Classification https://www.marktechpost.com/2019/06/24/deep-learning-with-keras-part-4-classification/
5. Convolutional Neural Networks https://www.marktechpost.com/2019/07/04/deep-learning-with-keras-part-5-convolutional-neural-networks/
6. Textual Data Preprocessing https://www.marktechpost.com/2019/09/13/deep-learning-with-keras-part-6-textual-data-preprocessing/
7. Recurrent Neural Networks https://www.marktechpost.com/2019/10/01/deep-learning-with-keras-part-7-recurrent-neural-networks/

MIDAS: Real-time Streaming Anomaly Detection in Dynamic Graphs (AI Paper Summary)
Paper: https://arxiv.org/abs/1911.04464
Github: https://github.com/Stream-AD/MIDAS
Presentation: https://www.youtube.com/watch?v=joPXrfZIJEM

NVAE: A Deep Hierarchical Variational Autoencoder
Arash Vahdat, Jan Kautz : https://arxiv.org/abs/2007.03898
#ArtificialIntelligence #DeepLearning #VariationalAutoencoder

Full Stack Deep Learning
Tobin et al.: https://course.fullstackdeeplearning.com
#ArtificialIntelligence #DeepLearning #MachineLearning

Online Lecture Series, Techfest, IIT Bombay is back with another highly inspiring leader, 𝗔𝗻𝗱𝗿𝗲𝘄 𝗡𝗴!

When it comes to rising fields like machine learning, artificial intelligence and computer vision, Andrew Yan-Tak Ng is one of the names you hear first.

Being the 𝗖𝗼-𝗙𝗼𝘂𝗻𝗱𝗲𝗿 𝗼𝗳 𝗖𝗼𝘂𝗿𝘀𝗲𝗿𝗮 and 𝗱𝗲𝗲𝗽𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴.𝗮𝗶 , he has taught millions of eager learners worldwide through his online courses. He is also the mastermind behind 𝗚𝗼𝗼𝗴𝗹𝗲 𝗕𝗿𝗮𝗶𝗻, a deep learning research team at Google which combines open-ended machine learning research with information systems and large-scale computing resources.

Professor of Computer Science and Electrical Engineering at 𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆, he has undertaken several research projects related to data mining and machine learning. His work has earned him several awards and he has gifted the world of technology with hundreds of his published papers.

Watch Prof. Andrew Ng talk about his life journey and experience, and the future of AI and its impact on the society with 𝗣𝗿𝗼𝗳. 𝗣𝗿𝗲𝗲𝘁𝗵𝗶 𝗝𝘆𝗼𝘁𝗵𝗶, CSE Department, IIT Bombay as host on 𝗧𝗲𝗰𝗵𝗳𝗲𝘀𝘁’𝘀 𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝗖𝗵𝗮𝗻𝗻𝗲𝗹 on 𝟭𝟭𝘁𝗵 𝗝𝘂𝗹𝘆 𝟮𝟬𝟮𝟬 at 𝟳 𝗣𝗠 𝗜𝗦𝗧.
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Link for the session - https://youtu.be/IpuocVMUOR0
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papers CVPR 2020

[https://www.youtube.com/watch?v=T82LYbWr_oc](https://www.youtube.com/watch?v=T82LYbWr_oc)