Launching New #free courses in Data Science - Start your journey and join the next generation of data scientists.

Course 1 : Introduction to Neural Networks
Link : https://buff.ly/2VvfNIU

Course 2 : Introduction to Natural Language Processing
Link : https://buff.ly/2VsA2Xl

Course 3 : A comprehensive Learning Path to become Data Scientist in 2019
Link : https://buff.ly/2So4krY

Course 4 : A comprehensive path for learning Deep Learning in 2019
Link : https://buff.ly/2ty7D5Y

Course 5 : Twitter Sentiments Analysis
Link : https://buff.ly/2EqLvAD

Course 6 : Creating Time Series Forecast using Python
Link : https://courses.analyticsvidhya.com/courses/creating-time-series-forecast-using-python/

Course 7 : Loan Prediction Practice problem
Link : https://courses.analyticsvidhya.com/courses/loan-prediction-practice-problem-using-python/

Course 8 : Big mart Sales Problem using R
Link : courses.analyticsvidhya.com/courses/big-mart-sales-prediction-using-r/

Next generation of phone will support up to 4.6 Gbs of data transfer on 5G. At this speed #AI #Edge computing may become irrelevant. You may want to create cloud solutions to stay on the edge.
https://youtu.be/wnck3d-zLdc

Neural Networks for Machine Learning by Geoffrey Hinton @geoffreyhinton (Coursera 2013)

Video Lectures:

https://www.youtube.com/watch?v=2fRnHVVLf1Y&list=PLiPvV5TNogxKKwvKb1RKwkq2hm7ZvpHz0 …


#ArtificialIntelligence #DeepLearning #NeuralNetworks #MachineLearning

Feature mapping in a quantum state space. "It remains to be seen whether the way in which Havlíček et al. represent data in quantum space is actually useful for real-world machine-learning applications."https://www.nature.com/articles/d41586-019-00771-0

RI Seminar: Amir Barati Farimani : Creative Robots with Deep Reinforcement Learning


https://www.youtube.com/watch?v=FwskZnxoBJI&feature=youtu.be

CS230 Deep Learning
Stanford's CS230 with lecture videos and more

Course Website:https://onlinehub.stanford.edu/cs230

"Inferring the function performed by a recurrent neural network"
Chalk et al.: https://www.biorxiv.org/content/biorxiv/early/2019/04/05/598086.full.pdf
#artificialintelligence #deeplearning #machinelearning

What's the best way to deploy Google BERT

(https://ai.googleblog.com/2018/11/open-sourcing-bert-state-of-art-pre.html

Yoshua Bengio On AI Priors and Challenges
In Synced. Author: Tingting Cao | Editor: Michael Sarazen : https://syncedreview.com/2019/02/16/yoshua-bengio-on-ai-priors-and-challenges/
#ArtificialIntelligence #DeepLearning #MachineLearning

Project Jupyter is a huge hit in data science, but it has not yet found widespread adoption in robotics. Today, we are releasing the first version of jupyter-ros, a collection of Jupyter interactive widgets inspired by Qt and RViz, to bring their features to the Jupyter ecosystem. This may be the right time for Jupyter-based developer tools, as cloud robotics is taking off."
Blog by Wolf Vollprecht:

https://blog.jupyter.org/ros-jupyter-b7e82b5e1202


#Robotics #Python #RobotOperatingSystem #Visualization #CloudRobotics

The power of deeper networks for expressing natural functions
David Rolnick & Max Tegmark: https://arxiv.org/abs/1705.05502
#DeepLearning #MachineLearning #NeuralComputing

Music Transformer


arxiv.org/abs/1809.04281

#DeepLearning #Transformer #MachineLearning #SpeechProcessing #Music

Reinforcement Learning with Attention that Works: A Self-Supervised Approach"
Manchin et al.: https://arxiv.org/abs/1904.03367

"That’s where an algorithm can help: once trained, it could reliably catch congenital heart disease in perpetuity. Catching heart defects early can lead to better outcomes for patients after birth. And if certain types of lesions are spotted in a fetal ultrasound, doctors can recommend in-utero therapies that significantly improve the heart’s condition by birth."

https://blogs.nvidia.com/blog/2019/03/21/ucsf-heart-defects-ai/?

The quantum physics community makes the ML community look like a bunch of beginners.
While we're arguing about the importance of reproducibility they *experimentally prove that there is no such thing as observer-independent objective truth*" - Ferenc Huszar
A quantum experiment suggests there’s no such thing as objective reality:
https://www.technologyreview.com/s/613092/a-quantum-experiment-suggests-theres-no-such-thing-as-objective-reality/
#MachineLearning #Physics #QuantumMechanics

Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks"
Pascual et al.
Paper: https://arxiv.org/abs/1904.03416
Code: https://github.com/santi-pdp/pase

Open Questions about Generative Adversarial Networks https://distill.pub/2019/gan-open-problems/ https://t.iss.one/ArtificialIntelligenceArticles

Repurposing CNNs - from images to sound:

Cool article from 2017 by Hershey et al. (https://arxiv.org/abs/1609.09430). Those nice folks took best of the best CNN for image recognition and repurposed them to identify audios. And, no wander, they succeeded.

What else looks like audio? Right, seismograms! Now I can't wait to implement ResNet for earthquake classification (which is already done btw

Step Change Improvement in Molecular Property Prediction with PotentialNet

Paper on a significant improvement in ability to predict molecular properties in drug design. #ML algorithms are getting better and better than classical methods.

Link: https://medium.com/@pandelab/step-change-improvement-in-molecular-property-prediction-with-potentialnet-f431ffa32a2c

#drugsdesign #biolearning #healthcare

Remember the black hole in the movie Interstellar? Turns out it was accurately modelled using Einstein's equations and 40000 lines of C++ code... and there's a full-on physics paper describing their process here: https://arxiv.org/pdf/1502.03808.pdf


#astrophysics #GravitationalLensing

Unsupervised learning: the curious pupil"
Unsupervised learning, a paradigm for creating artificial intelligence that learns about data without a particular task in mind: learning for the sake of learning.
Blog by Alexander Graves and Kelly Clancy, DeepMind: https://deepmind.com/blog/unsupervised-learning/
#artificialintelligence #deeplearning #unsupervisedlearning