Now introducing Chrome extension that makes it easy to find code when browsing arxiv.org or Google Scholar:

Really short and brief, yet useful #tutorial on #PyTorch #transferlearning

Transfer learning is a concept of using network trained for a certain task for another one.

Link: https://medium.com/@iamHarin17/transfer-learning-in-pytorch-f7736598b1ed

#DL #novice #entrylevel #beginner

Time series basics

Time series — data, with points having timestamps. Some might think that #timeseries are mostly used in algorithmic trading, but they often used in malware detection, network data analysis or any other field, dealing with some flow of time-labeled data. These two resources provide deep and easy #introduction into #TS analysis.

Github: https://github.com/akshaykapoor347/Time-series-modeling-basics
Data Camp presentation: https://s3.amazonaws.com/assets.datacamp.com/production/course_5702/slides/chapter3.pdf

#beginner #novice #python #entrylevel

​​Open AI releasing MMO.

Spoiler: it is not MMORPG. It is Massively Multiagent Mame environment for reinforcement learning agents. It will allow to develop something what for #trueAI will be like an amoeba to human. But it’s live now.

Link: https://blog.openai.com/neural-mmo/
Github: https://github.com/openai/neural-mmo
3DClient github: https://github.com/jsuarez5341/neural-mmo-client

#OpenAI

By Jupyter--Is This the Future of Open Science?
--> kutt.it/wi1wCM

Say hello to the Developer Release of MainframeOS! 👩‍💻 💪🔥 Get all the details on the blog, and be sure to check out our documentation before diving in. And let us know what you build with Mainframe! https://blog.mainframe.com/mainframe-os-launch-2019-71689d0c5ec #blockchain #crypto #crryptocurrency $MFT

#education #school : Начался набор в международную летнюю школу по машинному обучению: “Machine Learning Summer School” (MLSS)
В этот раз школа пройдет в Москве на территории Skoltech (Сколково)
Даты летней школы: 26 (понедельник) августа 2019 - 6 (пятница) сентября 2019
Подачи заявок: до 6 (понедельник) мая 2019
Место: Skoltech, Сколково, Москва
Язык обучения - английский

Основная аудитория: аспиранты. но рассматривают как мастеров так и окончивших образование
Сборы: 400/550/1000 евро для студентов/постдоков и преподавателей/остальных (в том числе работающих в индустрии)
Возможны спонсорское стипендиальное покрытие (полное или частичное (25%))
Организаторы: Фернандо Перес Круз, Евгений Бурнаев, Родриго Ривера Кастро

Предварительные темы:
Kernels - Arthur Gretton
Fairness & Interpretability - Isabel Valera
Causality - Joris Mooij
3D Deep Learning - Justin Solomon
Optimal Transport - Marco Cuturi
To be confirmed - Mark Girolami
Graph Neural Networks - Michael Bronstein
ML for Magnetic Resonance Imaging - Michel Besserve
Online Learning - Nicolò Cesa-Bianchi
Reinforcement Learning - Shimon Whiteson
Topological Data Analysis - Ulrich Bauer
Bayesian Deep Learning - Yarin Gal

Сайт школы: http://xxtt.ru/mlss2019

Octagon as positions marker. A.I drones circling in sync protecting/detecting/autonomous. Everything cubed in box with multiples possible usages.

Modern Deep Learning Techniques Applied to Natural Language Processing

Online collaborative book

Link: https://nlpoverview.com/index.html
Github: https://github.com/omarsar/nlp_overview
ArXiV: https://arxiv.org/abs/1708.02709

#NLP #beginner #novice #entrylevel #DL

Machine learning can boost the value of wind energy
http://bit.ly/2EKWIfH

Kids’ brains may hold the secret to building better AI
http://bit.ly/2VyXKku

We have stumbled into the era of machine psychology
http://bit.ly/2VvU5DX

MIT's introductory course on deep learning methods and applications.
http://bit.ly/2ELDnuZ

Game of Thrones in Words
https://tabsoft.co/2VAY1n3

The military wants to build a bullshit detector for social science studies
http://bit.ly/2EJqJwt

Humanity + AI: Better Together
http://bit.ly/2VxKpsA

Seven Myths in Machine Learning Research
http://bit.ly/2VBwbaq

Interpretable Machine Learning. A Guide for Making Black Box Models Explainable. Book by Christoph Molnar
http://bit.ly/2EIXWrL

Various views of variability
http://bit.ly/2EJGnaU

#Google has open-sourced #FederatedLearning code

Step-by-step #tutorial showing how to perform Federated Learning using the same infrastructure Google
uses on 10s of millions of smartphones.

Link: https://medium.com/tensorflow/introducing-tensorflow-federated-a4147aa20041

Web data scraping with Python by Brian Keegan University of Colorado, 2019.
Enjoy scraping web with detailed tutorial

​​Brilliant thread on ROC curve usage

ROC curve is used to measure how good is the discrimination between two distributions. This is a nice thread to refresh your memory, or to finally understand how ROCAUC works.

Link: https://threadreaderapp.com/thread/1104134423673479169.html
An introduction to prediction research: http://www.cecilejanssens.org/wp-content/uploads/2018/01/PredictionManual2.0.pdf

#ROC #AUC

Lessons learned building natural language processing systems in health care

It’s suprising, but #NLP in #healthcare doesn’t work the same way, as a researcher might expect, because of semantic.
Lesson #1: Off-the-shelf NLP models don’t work
Lesson #2: Build trainable NLP pipelines
Lesson #3: Start with labeling ground truth

Link: https://www.oreilly.com/ideas/lessons-learned-building-natural-language-processing-systems-in-health-care

​​Website using Deep Learning to colorize pictures.

Link: https://colourise.sg/#colorize

#DL #CV #demo

Boom! What to read on the weekend, Issue #53

Humor is both a hurdle and a gauge to improve AI, human interaction
http://bit.ly/2EJtca1

How to Choose the Right Chart Type [Infographic]
http://bit.ly/2EJPI2A

Will Artificial Intelligence Form a Singleton or Will There Be Many AGI Agents? – An AI Researcher Consensus
http://bit.ly/2EJGCCQ

Half a million x-rays! First impressions of the Stanford and MIT chest x-ray datasets
http://bit.ly/2EI95sL

CS294-158 Deep Unsupervised Learning Spring 2019
http://bit.ly/2VyMtRm

7 Steps to crack your first Data Science Internship (Tips, Tricks and Resources!)
http://bit.ly/2EIJoZk

Here’s who has the most juice in Twitter’s AI influencer community
http://bit.ly/2VtxibO

The 2019 Data Science Dictionary – Key Terms You Need to Know
http://bit.ly/2VFcMp5

TensorFlow Conv2D Layers: A Practical Guide
http://bit.ly/2VvJ3yA

Map of bus routes in Singapore stacked one on top of the other
http://bit.ly/2VCrkpp

Boom! Weekly selection from DSB. Issue #44
The TOP 10 most popular links for the week

1. Best Deep Learning Books: Updated for 2019
http://bit.ly/2EHy2oc

2. Game of Thrones in Words
https://tabsoft.co/2VAY1n3

3. A Data Cleaner`s Cookbook
http://bit.ly/2EKyi60

4. MIT's introductory course on deep learning methods and applications.
http://bit.ly/2ELDnuZ

5. The military wants to build a bullshit detector for social science studies
http://bit.ly/2EJqJwt

6. We have stumbled into the era of machine psychology
http://bit.ly/2VvU5DX

7. Interpretable Machine Learning. A Guide for Making Black Box Models Explainable. Book by Christoph Molnar
http://bit.ly/2EIXWrL

8. China’s Tech Firms Are Mapping Pig Faces
https://nyti.ms/2VAbfAy

9. Machine learning can boost the value of wind energy
http://bit.ly/2EKWIfH

10. General Assembly's Data Science course in Washington DC
http://bit.ly/2VxZWIT