Machine learning application (Kartal)
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1- Participate in cutting edge research in machine learning applications.
2- Apply your expertise in biometrics, Natural Language Processing, computer vision and real-time data mining solutions.

Admin: @Kartal_ai (https://xn--r1a.website/Kartal_ai )
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Being in EAB winter workshop is one of the best opportunity to get more knowledge about presentation attacks detection(PAD) in idiap research institute. Today we learnt about #biometric challenges and #face PAD.
@euro_biometrics
@AMBERBiometrics
#MachineLearning https://t.co/TD9Sy6JmQG
برای اینکه بتونید عملی روی موبایل و امبدد سیستم ایپلمنت کنید حتما این ایسپشالیزشن رو ببینید....
I found Tensorflow:Data and Deployment specialization very interesting and useful especially for mobile biometric researchers who is going to implement #biometrics on mobile devices.
#MachineLearning

@AMBERBiometrics
@deeplearningai_
@euro_biometrics
https://t.co/18CS4PhjEg

https://twitter.com/jalilnkh/status/1240034616217649153?s=09
مرسی گوگل که آرزومو براورد کردی. دیگه نابینایان عزیز هم می تونند دنیا رو حس کنند.

When I became 22-year old I start thinking of a #machine to help blind people I couldn't achieve. But it was always a dream for me to do it.Thanks,
@Google
for making my wishes true.

Google AI to create a set of AI-powered spectacles that help blind and visually-impaired people to see. The glasses extract visual information about images of people, belongings, and public transport, and then speak about them out loud. Let’s have a brief discussion on this technique. Reference :
https://www.i2tutorials.com/googles-artificial-intelligence-powered-smart-glasses-help-the-blind-to-see/?fbclid=IwAR3nsRIyxQiVj6tFWARk9qzt_opii-PiDC5t6A7J05uLWTLU8nB9zIcTNtI

#python #machinelearning #artificialintelligence #datascience #computervision #googleAI
#AIpoweredspectacles #blind #impairedpeople #software #opticalcharacterrecognition

کانال:
https://xn--r1a.website/Machinelearning_Kartal
Great talk, I have listened twice. Happy birthday to you dear scientist Andrew Ng @andrewyng .

I completely agree with your comment. Most fields have been suffered because of fewer data. According to my little experience, It is hard to collect data for biometric recognition systems and for the structure of individual molecules. For sure there is a bunch of these applications which are not easy to collect more data. However, I would like to mention algorithm developments in terms of interpretability machine learning. We have great neural networks but we still cannot trust the existing methods in high-risk applications.



Again thank you scientist Andrew Ng. It is a great pleasure to watch your updates about AI.

Best Regards
Jalil Nourmohammadi Khiarak

#machinelearning #ai #datascience #deeplearning #deeplearning #artificialintelligence #neuralnetworks #neuralnetworks #data #bigdata #ml #thankyou #analytics #dataanalytics #algorithms #experience #biometrics #facerecognition #medicalimaging


https://www.youtube.com/watch?v=06-AZXmwHjo



کانال:
https://xn--r1a.website/Machinelearning_Kartal
I passed first step ☺️ 100 citations. Always happy to collaborate and cooperate with teams. Hope to reach 1000 citations.
#paper
#article
#AI
#DataScience
#MachineLearning
#biometric
https://scholar.google.com/citations?user=_I3xMO8AAAAJ&hl=en
En 🇺🇸:
Andrew NG (Andrew Ng ):

Sometimes I have seen some #business teams push a #machinelearning team to guarantee that their learning #algorithm will be 80% accurate, 90% accurate or 99% accurate before the machine learning team had a chance to establish a rough baseline. This unfortunately puts machine learning team in a very difficult position. If you are in that positions I would urge you to consider pushing back and asking for time to establish rough baseline performance before giving a more firm prediction about how accurate the machine learning system can eventually get to be.

Source:
https://lnkd.in/dwgr-HQA

تۆرکجه 🇮🇷:
آندرو اینگ دئیر:
بعضی زامانلار گورمیشم بعضی بیزینس تیملری ایستیرلر ماشین اؤیرنمه تیملرین الگوریتم لری بیر بئیس لاین سیستم تحویل ورمیمیش ۸۰٪، ۹۰٪ یادا ۹۹٪ دیقته چاتا. بو تاسفله ماشین اؤیرنمه تیملرین بیر چتین موقعیته سالیر. اگر سیز بو موقعیت ده سیز، سیزدن ایستیرم بیر قدم دالا اوتورون و بیردنه بئیس لاین دیقت ورن سیستمی چیخادماقا زامان ایستئیون. اونان قاباق چالیشیب ماشین اؤیرنمسینه دیقت پیش بینی المق یاخشی ائده دئیل.
قایناق:
https://lnkd.in/dwgr-HQA

چئورن:
جلیل کارتال

کانالیمیز:
https://xn--r1a.website/JalilKartal
Andrew Ng notes in Machine learning engineering for production about labeling data:

1- Options : In - house vs. outsourced vs. crowdsourced.
2- Having MLEs label data is expensive . But doing this for just a few days is usually fine .
3- Who is qualified to label ?
4- Don't increase data by more than 10x at a time.

I would say thank you for the best advice.

#machinelearning #engineering #data DeepLearning.AI
Workera
#deeplearning #ai #datascientist


کانالیمیزی جانلی یایین:

https://xn--r1a.website/Machinelearning_Kartal
#اپلای #ماری_کوری

فارسی: ماری کوری از بهترین فاندها هست که ایرانیان شانس بیشتری برای قبولی دارند به مدرک زبان احتیاج نیست. تازه بیشترین پول و ساپورت هنگام کار در اروپا برای خارجی ها داره خیلی هم دانشجویان کشور مقصد حسودی دانشجویان فاند ماری کوری می کنند.


تۆرکجه: ماری کوری ایرانلیلارین قبول اوْلماق شانسی‌نین داها یۆکسک اوْلدوغو ان یاخشی فاندلاردان بیریدیر، هئچ بیر دیل سئرتیفیکاتی طلب اوْلونمور. یئنیجه، آوروپادا ایشله‌یرکن اجنه‌بیلر اۆچون ان چوخ پۇل و دستک وار و تعیینات اؤلکه‌نین بیر چوخ طلبه‌سی ماری کۇری طلبه‌لرینه قؽسقانجلیقلا یاناشیر.

https://www.linkedin.com/posts/holger-fr%C3%B6hlich-4722814_aipd-ai-parkinsondisease-activity-7266729473247514626-MCKt?utm_source=share&utm_medium=member_android


کانالیمیزی جانلی یایین:
https://xn--r1a.website/Machinelearning_Kartal