​CURL: Contrastive Unsupervised Representations for Reinforcement Learning

@Machine_learn
This paper introduces a new method that significantly improves the sample efficiency of RL algorithms when learning from raw pixel data.


Paper: https://arxiv.org/abs/2004.04136.pdf
Code: https://github.com/MishaLaskin/curl


#rl #agent #reinforcement #learning

@Machine_learn

GPT-3: Language Models are Few-Shot Learners

Github: https://github.com/openai/gpt-3

Paper: https://arxiv.org/abs/2005.14165v1

Praise for Deep Learning Illustrated
#book #DL

@Machine_learn

@Machine_learn

Acme: A research framework for reinforcement learning

Github: https://github.com/deepmind/acme

Paper: https://arxiv.org/abs/2006.00979

First Contact with Deep Learning Practical Introduction with Keras
#book #keras #DL
@Machine_learn

A Smooth Representation of SO(3) for Deep Rotation Learning with Uncertainty

@Machine_learn

Website: https://papers.starslab.ca/bingham-rotation-learning/

Paper: https://arxiv.org/abs/2006.01031

Github: https://github.com/utiasSTARS/bingham-rotation-learn

Neural Networks and Deep Learning
A Textbook
#book #DL
@Machine_learn

@Machine_learn

YOLOv5 is Here: State-of-the-Art Object Detection at 140 FPS
https://blog.roboflow.ai/yolov5-is-here/

Github: https://github.com/ultralytics/yolov5

GCP Quickstart: https://github.com/ultralytics/yolov5/wiki/GCP-Quickstart

@Machine_learn

AR-Net: A simple autoregressive NN for #timeSeries


blog: https://ai.facebook.com/blog/ar-net-a-simple-autoregressive-neural-network-for-time-series/
paper: https://arxiv.org/abs/1911.03118

@Machine_learn

VirTex: Learning Visual Representations from Textual Annotations

https://kdexd.github.io/virtex/

Github: https://github.com/kdexd/virtex

Paper: arxiv.org/abs/2006.06666

Deep Learning with TensorFlow 2 and Keras
Second Edition
#book #keras #DL #tensorflow

@Machine_learn

Segmentation Loss Odyssey

@Machine_learn

Github: https://github.com/JunMa11/SegLoss

Paper: https://arxiv.org/abs/2005.13449v1

Hands-On Meta Learning with Python
#tensorflow #ML
#book
@Machine_learn

Python for Signal Processing
#book #python
@Machine_learn

@Mchine_learn

Neural Manifold Ordinary Differential Equations

Article: https://arxiv.org/abs/2006.10254

Github: https://github.com/CUVL/Neural-Manifold-Ordinary-Differential-Equations

@Machine_learn


BentoML

BentoML is an open-source platform for high-performance ML model serving.

https://github.com/bentoml/BentoML
bentoml/BentoML

Denoising Diffusion Probabilistic Models

@Machine_learn

https://hojonathanho.github.io/diffusion/

Github: https://github.com/hojonathanho/diffusion

Paper: https://arxiv.org/abs/2006.11239