Juicy Data

​​Solving classic unsupervised learning problems with deep neural networks

Discusses ideas from two recent papers: Learning gradient-based ICA by neurally estimating mutual information and Gradient-Based Training of Slow Feature Analysis and Spectral Embeddings

🔎Blogpost: http://bit.ly/33R99An
#⃣ #deeplearning #embeddings #unsupervisedlearning

​​NERD : Evolution of Discrete data with Reinforcement Learning

A toy project aimed at evolving sequence using an algorithm which is the combination of both Genetic Algorithm and Reinforcement Learning. The aim of the project was to evolve SMILES chemical molecules from scratch.

📍GitHub: https://github.com/Gananath/NERD
🔖Blog https://gananath.github.io/nerd.html
#⃣ #rl #project #dl #nerd

​​Clash of Frameworks: PyTorch vs Tensorflow

A researcher at Cornell University compared references to TensorFlow and PyTorch in public sources over the past year. PyTorch is growing rapidly within the research community, while TensorFlow maintains an edge in industry, according to the report.

🔍Blogpost: http://bit.ly/2oDPsNB
#⃣ #research #analysis #pytorch #tf #tensorflow

​​Solving Rubik’s Cube with a Robotica Hand

OpenAI trained a pair of neural networks to solve the Rubik’s Cube with a human-like robot hand. The nets are trained entirely in simulation, using the same reinforcement learning code as OpenAI Five paired with a new technique called Automatic Domain Randomization (ADR).

📃Paper: http://bit.ly/2OREuyp
🚩All Videos: http://bit.ly/35FRzRk

🔎Blogpost: https://openai.com/blog/solving-rubiks-cube/
#⃣#openai #rl #adr

​​ML Career Advice and Reading Papers

One hour Andrew Ng's CS230 Lecture on Deep learning has been summarised into concise 5 minutes and was written in a spirit to retain what was said and largely to look back and implement it.

Material will help to navigate a career in ML/DL and to learn how to read research papers.

💻 CS 230 Lectures: http://cs230.stanford.edu/lecture/

🔎Blogpost: http://bit.ly/35AWNy4
#⃣ #beginner #dl #deeplearning #cs230

​​Microsoft open sources SandDance, a visual data exploration tool

By using easy-to-understand views, SandDance helps you find insights about your data, which in turn help you tell stories supported by data, build cases based on evidence, test hypotheses, dig deeper into surface explanations, support decisions for purchases, or relate data into a wider, real world context.

⚠ Preview: https://sanddance.js.org/
🐱 Git: https://github.com/Microsoft/SandDance

🔍 Blogpost: http://bit.ly/31bWO7Y
#⃣ #js #sandance #microsoft

​​PyTorch Mobile: Deployment on iOS and Android

Support (and corresponding packages) to deploy PyTorch models directly to mobile devices for inference was added with the latest PyTorch 1.3 release.

🔎 Overview: https://pytorch.org/mobile/home/

📱iOS: https://pytorch.org/mobile/ios/
☎ Android: https://pytorch.org/mobile/android/

#⃣ #pytorch #package #python #mobile