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DataScienceLab
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Innovation and Data Science Lab
CS Department of Amirkabir University of Technology
idatascience.ir
Director: Dr.mohammad Akbari
any Question: @ahforoughi
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آمازون (Amazon)‌ خبر داده چندتا از کورس‌های یادگیری ماشین خودش که برای آموزش کارکنان‌شون تهیه شده‌بودن رو برای استفاده عمومی در اختیار گذاشته.

https://www.amazon.science/latest-news/machine-learning-course-free-online-from-amazon-machine-learning-university

این آموزش‌ها که در سه بخش بینایی‌ماشین، پردازش زبان طبیعی و کار با جداول داده هستند رو می‌تونید در صفحه یوتیوب Amazon's Machine Learning University در آدرس زیر مشاهده کنید:

https://www.youtube.com/channel/UC12LqyqTQYbXatYS9AA7Nuw
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رابط AUX مبتنی بر مدل زبانی GPT-3 میتونه هر مثال منطقی رو به دستور برای خط فرمان تبدیل کنه. مثال ها رو میتونید ببینید:
$ aux compress current folder to arch.tar.gz
tar -zcvf arch.tar.gz .

$ aux create new branch dev_ui in git
git checkout -b dev_ui

$ aux count number of lines in file.txt
wc -l file.txt

$ aux create lambda function myfunc in aws
aws lambda create-function --function-name myfunc


https://news.1rj.ru/str/cvision
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Tesla Autopilot on the Road!!

Tesla is using PyTorch for distributed CNN training.

Source 👉 https://lnkd.in/eZqzurQ
@Ai_Tv
Forwarded from کانال اطلاع‌رسانی آزمایشگاه سپهر (Ali Reza Feizi Derakhshi)
#فراخوان_مقاله

مجله:
Pattern Recognition

عنوان:
Masked Face Recognition and Touchless Biometrics at the time of COVID-19

موضوعات:
1. Face image reconstruction from masked faces
2. Partial face recognition from near-infrared and/or thermal images
3. Periocular biometrics
4. Iris recognition in the visible spectrum
5. Eye blink and gaze analysis
6. Pupil dynamics for biometric recognition
7. Face dynamics from occluded face images
8. Ear recognition
9. Touchless fingerprint recognition
10. Novel biometrics for minimizing infection transmission

لینک فراخوان

لینک مجله

@cominsys_channel
🎉🥳DataFest2020 THIS WEEK🥳🎉

Get reeeeeeady! You probably noticed that we published LESS content than usual because we were preparing something speciiiiiiialll.

Now we present you amazing: https://fest.ai

Open!
Free!
Online!
Data Science event open for everyone!

Book upcoming weekends for something worthy!

Link: https://fest.ai/2020/
لینک فرم: link
Forwarded from Catalyst | Community
​​Official announcement 🎉
We are launching new open source deep learning course with Catalyst.
Course notebooks and assigments will be in English. Lectures and seminar videos - in Russian (we are working on their translation).

Catalyst is a PyTorch ecosystem framework for Deep Learning research and development. It focuses on reproducibility, rapid experimentation and codebase reuse. This means that you can seamlessly run training loop with metrics, model checkpointing, advanced logging and distributed training support without the boilerplate code.

In this course we will dive into back-propagation algorithm. After that we will go through computer vision, generative adversarial networks and metric learning tasks. We will also talk about NLP and RecSys best practices with RL applications for them. Last but not least, we will speak about day-to-day engineering tricks, that every MLE should know about. During the course you will need to pass several kaggle competitions and deploy our own machine learning microservice in the end of the course.

Join our slack and let's accelerate your DL RnD with Catalyst 🚀

Github: https://github.com/catalyst-team/dl-course
Stepik: https://stepik.org/course/83344
Slack: https://join.slack.com/t/catalyst-team-core/shared_invite/zt-d9miirnn-z86oKDzFMKlMG4fgFdZafw
International AI Finland virtual conference 30.9.2020
The AI Finland 2020 event is an international virtual conference focusing on business research collaboration in AI. The aim is to create an AI Finland concept that brings together companies and top-level research instances in different themes and areas each year. The AI Finland event starts in Tampere, the heart of Finnish industry scene, and focuses thus on sustainable smart production.
https://tampere.ai/en/ai-finland-2020-en/
Major new features of the 3.9 series, compared to 3.8
Some of the new major new features and changes in Python 3.9 are:

- PEP 573, Module State Access from C Extension Methods
- PEP 584, Union Operators in dict
- PEP 585, Type Hinting Generics In Standard Collections
- PEP 593, Flexible function and variable annotations
- PEP 602, Python adopts a stable annual release cadence
- PEP 614, Relaxing Grammar Restrictions On Decorators
- PEP 615, Support for the IANA Time Zone Database in the Standard Library
- PEP 616, String methods to remove prefixes and suffixes
- PEP 617, New PEG parser for CPython
- BPO 38379, garbage collection does not block on resurrected objects;
- BPO 38692, os.pidfd_open added that allows process management without races and signals;
- BPO 39926, Unicode support updated to version 13.0.0;
- BPO 1635741, when Python is initialized multiple times in the same process, it does not leak memory anymore;
- A number of Python builtins (range, tuple, set, frozenset, list, dict) are now sped up using PEP 590 vectorcall;
- A number of Python modules (_abc, audioop, _bz2, _codecs, _contextvars, _crypt, _functools, _json, _locale, operator, resource, time, _weakref) now use multiphase initialization as defined by PEP 489;
- A number of standard library modules (audioop, ast, grp, _hashlib, pwd, _posixsubprocess, random, select, struct, termios, zlib) are now using the stable ABI defined by PEP 384.
سلام
آزمایشگاه علوم داده برای یک پروژه صنعتی نیاز به یک نفر آشنا به تهیه طرح کسب و کار (business plan) و آشنا به نرم افزار Comfar است. علاقمندان با من تماس بگیرند.
DataScienceLab
https://twitter.com/alfcnz/status/1306789982816940033?s=19
دوره‌ی deep learning دانشگاه NYU که توسط Yann LeCun و Alfredo Canziani ارائه شد و به 11 زبان دنیا از جمله فارسی موجوده:

انگلیسی:
https://atcold.github.io/pytorch-Deep-Learning/

فارسی:
https://atcold.github.io/pytorch-Deep-Learning/fa/

✳️تشکر ویژه از تمام کسانی که در ترجمه فارسی کمک کردند