Why Excel Users Should Learn Python : https://t.co/XwF1IbqYy0 #abdsc #BigData #Analytics #DataScientists #Coding

So, check out this "Complete Tutorial To Learn #DataScience With #Python From Scratch": https://t.co/PfQ5gfcke5 #MachineLearning #AI #Algorithms

This algorithm browses Wikipedia to auto-generate textbooks https://t.co/bExALBY6u0

#DeepLearning #MachineLearning #AI #DataScience

⚠ A mathematical model from 103 years ago predicted something that was seen for the first time today: a #black_hole.

#MachineLearning could never do that: it needs observations to model anything. This is a major weak-point of ML. Let's fix it.

A stark contrast between Machine Learning vs other forms of mathematical modeling is that ML models often don't model extreme corner cases very well, because #data in those areas is rare. Gathering data in important areas is as important a skill as building fancy neural networks.

Sadly, too often, using extreme inputs to a model is more useful: e.g. by modeling physics of levers on light objects with short levers, we then built very long levers to lift extremely heavy things. Instead, ML is better suited at modeling everyday phenomena with complex models.

https://twitter.com/Reza_Zadeh/status/1053771110410375168?s=19

🏆 This Google Tutorial (96 slides total) on #MachineLearning is the best:

https://t.co/hsn9U4Yh9X

🍟 Data science summer school this September in Pisa, Italy. It is straighter than it looks.

https://t.co/gZQdBpp8O5

🌀 Machine learning is a great tool to solve problems, but how does it compare to traditional mathematical modelling? Does one win out or is there a way to combine the two?

https://andrewmellor.co.uk/blog/articles/2019/05/09/machine-learning/

#machinelearning #mathematics #datascience #pytorch #python #collab

Time Series Analysis From the Ground Up

You can now download the slide deck from our Intro to Time Series tutorial:

https://t.co/6AiGOPZAlh

#Data Science #Timeseries #ARIMA #MachineLearning #Tutorial

💰 We are looking for a #postdoc

https://www.fz-juelich.de/inm/inm-7/EN/Home/home_node.html

Join us to develop & apply new approaches for #MachineLearning on neuroimaging and clinical datasets.

Would you like to become an #highperformancecomputing expert? Would you like to become a #MachineLearning geek?

Join the @mhpc_sissa_ictp master held in Trieste by Sissa and ictp, two amazing scientific institutions! #Science #innovation #MachineLearning #aiforgood

standard #Applications for MHPC 2020/2021 are now open!
Here you can find the link to submit your application: https://t.co/aVPjQkT4bX

چهارشنبه ساعت۱۸:۳۰ به وقت تهران

What don’t we know about #machinelearning? Dive in with this Joint ICTP-SISSA Online Colloquium tomorrow, 22 July, at 16:00 CET!

Here’s all the info & how to join in 🎥 https://t.co/6VxNZLoy69

NeurIPS2020 workshop on 'Topological Data Analysis & Beyond' is open for submissions now:

https://t.co/4KhsCW0QXb

This is your chance to showcase work that combines #MachineLearning and #Topology.

💰 The deadline to apply for the PhD positions in KTH is approaching! #KTH #datascience #machinelearning #AI #PhD #PhDposition

https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:355118/type:job/where:4/apply:1

💰 We are currently looking for passionate Data Engineers and Data Scientists for our HQ in Berlin, who can improve food-delivery experience for millions of our customers, present in more than 40 countries!

You will develop innovative systems to automate marketing campaigns, design a tailored user experience for each customer and question the existing decision-making processes with ML and advanced analytics solutions.If you're a creative problem solver who is eager to deliver solutions and hungry for a new adventure, an international workplace is waiting for you in the heart of Berlin!

Senior data engineer (Python):
https://lnkd.in/dvzFPZU

Senior data scientist:
https://lnkd.in/dMaCQgC

#dataengineering #datascience #machinelearning #ml #data #deliveryhero

Quick peek at what the team does:
https://lnkd.in/dP2cuNf

“The Hitchhiker's Guide to #CondensedMatter and #StatisticalPhysics” is a series of virtual events that will provide a roadmap of current research directions in the field.

🔹 Register to the first virtual school on #MachineLearning for CM by November 30: https://t.co/WvX1sbYFwE

“The Hitchhiker's Guide to #CondensedMatter and #StatisticalPhysics” is a series of virtual events that will provide a roadmap of current research directions in the field.

🔹 Register to the first virtual school on #MachineLearning for CM by November 30: http://indico.ictp.it/event/9471/

💰 I'm hiring 2 graduate students for my ERC project, focused on predicting depression onset in 2,000 students. Looking for a #PhD position? Come work with me @UniLeiden!

Core topics: #depression, #complexity, #timeseries, #networks, #EMA, & #MachineLearning.

You can find the 2 positions in the link below.
https://t.co/jGQIPX2DuG

Here is a blog in which I describe the project in some more detail, including a short video. /
https://t.co/pdZx1k7xXW

Applications for ICTP full scholarships for the Master in High Performance Computing @mhpc_sissa_ictp for candidates from Developing Countries are now open!

Deadline: 30 April

MHPC is an innovative specialization program that prepares students for exciting careers in the fast-growing field of #HPC
#computing #highperformancecomputing #AI #MachineLearning #DeepLearning #programming #Algorithms
More info 👉 https://t.co/Jg2esS8hvY

ELLIS #PhD Program in #machinelearning now accepting applications (deadline: November 15, 2021). Details on the program and the application process here: https://t.co/XFgAYKclCs

Looking for a #postdoc in computational mechanics applied to #materials #physics and #biophysics. You'll also have the opportunity to learn and develop scientific #MachineLearning methods related to these problems. Check us out: https://t.co/df5oPmTm0C

AI4Science #Call for fellows!
Deadline: Oct. 31, 2022

The #Fellowship gives researchers the chance to collaborate EPFL faculties on accelerating the use and furthering the understanding of #MachineLearning methods in the scientific discovery process. You hold a PhD, in any field relevant to this endeavour, are fluent in English and have a collaborative spirit.

https://www.epfl.ch/research/domains/cis/call-for-fellows/