All the statistical distributions and how they relate to each other!

Source: https://www.math.wm.edu/~leemis/2008amstat.pdf

#distributions #visualization #cheatsheet #statistics

Free «Advanced Deep Learning and Reinforcement Learning» course.

#DeepMind researchers have released video recordings of lectures from «Advanced Deep Learning and Reinforcement Learning» a course on deep RL taught at #UCL earlier this year.

YouTube Playlist: https://www.youtube.com/playlist?list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs

#course #video #RL #DL

Paper Summary: Neural Ordinary Differential Equations
https://towardsdatascience.com/paper-summary-neural-ordinary-differential-equations-37c4e52df128

A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks. arxiv.org/abs/1907.02649

Measuring the Data Efficiency of Deep Learning Methods.

arxiv.org/abs/1907.02549

fixing a Major Weakness in Machine Learning of Images with Hinton’s Capsule Networks

https://www.kdnuggets.com/2019/05/machine-learning-images-hinton-capsule-networks.html

Joint Slot Filling and Intent Detection via Capsule Neural Networks


arxiv.org/abs/1812.09471

How Xnor.ai Managed to Squeeze a Deep Neural Network onto a $20 Wyze Camera

Blog by Carlo C del Mundo: https://medium.com/@xnor_ai/how-xnor-ai-managed-to-squeeze-a-deep-neural-network-onto-a-20-wyze-camera-88a5f9fc3466

#neuralnetwork #deeplearning #machinelearning

Two new benchmark papers for reinforcement learning have been published online!

[https://www.endtoend.ai/rl-weekly/24](https://www.endtoend.ai/rl-weekly/24)

Object-oriented programming for data scientists: Build your ML estimator
https://towardsdatascience.com/object-oriented-programming-for-data-scientists-build-your-ml-estimator-7da416751f64

A Tour of Generative Adversarial Network Models
https://machinelearningmastery.com/tour-of-generative-adversarial-network-models/

Simple Guide to Hyperparameter Tuning in Neural Networks
https://towardsdatascience.com/simple-guide-to-hyperparameter-tuning-in-neural-networks-3fe03dad8594

DeepView: generate new views having sparse set of input images from different viewpoints
arxiv.org/abs/1906.07316

Neural Rendering in the Wild:
1. Take ~3K Internet photos
2. Retrieve 3D point cloud from photos using any structure from motion algorithm
3. Enjoy realistic free-point-of-view video, rerendered by NN
arxiv.org/abs/1904.04290

Video Question Generation via Cross-Modal Self-Attention Networks Learning. arxiv.org/abs/1907.03049

Dependency-aware Attention Control for Unconstrained Face Recognition with Image Sets. arxiv.org/abs/1907.03030

One of the hardest problems in #AI is common sense reasoning. This paper by
Nazneen Fatema Rajani, Bryan McCann, Caiming Xiong, Richard Socher
arxiv.org/abs/1906.02361
Github: (link: https://github.com/salesforce/cos-e)
Blog: (link: https://blog.einstein.ai/leveraging-language-models-for-commonsense/)

15 Of The Best Machine Learning Courses On Coursera For Free
https://hackernoon.com/15-of-the-best-machine-learning-courses-on-coursera-for-free-d83ad23f54d7