"Deep Reinforcement Learning with Subgoals"#NIPS 2017
Invited talk by DeepMind’s Professor David Silver
https://vimeo.com/249557775 @ArtificialIntelligenceArticles

Practical Text Classification With Python and Keras

By Nikolai Janakiev: https://realpython.com/python-keras-text-classification/

Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares

By Stephen Boyd and Lieven Vandenberghe, Cambridge University https://web.stanford.edu/~boyd/vmls/

Complex-YOLO: Real-time 3D Object Detection on Point Clouds

Simon et al.: https://arxiv.org/abs/1803.06199

Capture Anything in 3D (Using Only Your Phone)

Copy + Paste reality: https://3dScannerApp.com @ArtificialIntelligenceArticles

pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference

Joshi et al.: https://arxiv.org/abs/1810.08854

Reconstructing quantum states with generative models"

Carrasquilla et al.: https://arxiv.org/abs/1810.10584

#quantumphysics #quantumcomputing #machinelearning #quantummachinelearning #artificialinte

Build your own robotic cat

Blog by Alex Bate: https://www.raspberrypi.org/blog/robotic-cat-petoi-nybble/

#Arduino #ArtificialIntelligence #MachineLearning #RaspberryPi #Robotics

SURREAL: Open-Source Reinforcement Learning Framework and Robot Manipulation Benchmark

https://surreal.stanford.edu/

BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop"

Maxime Chevalier-Boisvert et al.: https://arxiv.org/abs/1810.08272

NEP 18 — A dispatch mechanism for NumPy’s high level array functions

Abstact: "We propose the array_function protocol, to allow arguments of NumPy functions to define how that function operates on them. This will allow using NumPy as a high level API for efficient multi-dimensional array operations, even with array implementations that differ greatly from numpy.ndarray."

https://www.numpy.org/neps/nep-0018-array-function-protocol.html
#numpy

These enhancements enable us to process large 3D dark matter distribution and predict the cosmological parameters ΩM, σ8, and ns with unprecedented accuracy arxiv.org/abs/1808.04728

30 Amazing Machine Learning Projects https://medium.mybridge.co/30-amazing-machine-learning-projects-for-the-past-year-v-2018-b853b8621ac7 @ArtificialIntelligenceArticles

Ultimate guide and resources for Data science 2019

https://medium.com/@purnasaigudikandula/ultimate-guide-and-resources-for-data-science-2019-f663f9384fc7 @ArtificialIntelligenceArticles

CVPR Paper Controversy; ML Community Reviews Peer Review
https://medium.com/syncedreview/cvpr-paper-controversy-ml-community-reviews-peer-review-79bf49eb0547 @ArtificialIntelligenceArticles

TensorFlow.js Examples

GitHub repository containing examples in TensorFlow.js: https://github.com/tensorflow/tfjs-examples

#artificialintelligence #deeplearning #machinelearning #tensorflow

Using Machine Learning to Predict the Evolution of Physics Research

paper : https://arxiv.org/abs/1810.12116 @ArtificialIntelligenceArticles

New research group at Oxford Comp Sci!

Oxford Applied and Theoretical Machine Learning Group (OATML): https://oatml.cs.ox.ac.uk/

#artificialintelligence #bigdata #machinelearning #neuralnetworks

Efficiently measuring a quantum device using machine learning

Lennon et al.: https://arxiv.org/abs/1810.10042

#ArtificialInteligence #QuantumPhysics #Research #Physics #MachineLearning

Reinforcement Learning Will Be 2019's Biggest Trend In Data Science 😊🎉

Forbes: https://www.forbes.com/sites/quora/2018/10/26/reinforcement-learning-will-be-2019s-biggest-trend-in-data-science/#73d3