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://t.me/Kartal_ai )
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Here is a list of what I believe are the 10 Practical Steps for #DataScience:

1. Programming
a. Python - https://lnkd.in/gGQ7cuv
b. R - https://lnkd.in/giMGbph
c. SQL - https://lnkd.in/gM8nMNP
d. Command Line - https://lnkd.in/e3EQuis

2. Stats/Prob/Math
a. Coursera's Statistics w/ R - https://lnkd.in/gGT9NEf
b. edX's Probability - https://lnkd.in/gpUyC3P
c. Khan Academy Linear Algebra - https://lnkd.in/gMshbX4

3. Data Viz
a. Python Matplotlib- https://lnkd.in/gr3ifNt
b. R ggplot2 - https://lnkd.in/eThJXNr

4. Data Manipulation
a. Python Pandas - https://lnkd.in/g9kfpX4
b. R dplyr - https://lnkd.in/gAWusih

5. #MachineLearning
a. Google Crash Course - https://lnkd.in/gSgkVcT
b. Stanford Coursera - https://lnkd.in/g8ZG557
c. ISLR Book - https://lnkd.in/gk8GPZC

6. Experimental Design
a. Udacity A/B Testing - https://lnkd.in/gCerh4f

7. Business Sense
a. Metrics - https://lnkd.in/gZAG7bS

8. Communication
a. Storytelling - https://lnkd.in/gwjxVUu

9. Profile Building
a. GitHub - https://lnkd.in/g4r9naJ
b. LinkedIn - https://lnkd.in/g-KHHEC
c. Kaggle - https://lnkd.in/gBC77Hu
d. DS Resume - https://lnkd.in/gU8WVAF

🏅 10. Job Search
a. Daily Expert Tips & Advice - https://lnkd.in/g8z-xXD

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Hope this helps! 👍
Updated on my site - http://www.claoudml.co/

با تشکر از
Hossein narghani

کانال

https://t.me/Machinelearning_Kartal/1416
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://t.me/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://t.me/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
Forwarded from Jalil KartalOl
@AndrewYNg well said:
If you have a best model which have the best results on test set. Celebrate it 🥳 that's wonderful but be careful it is not always best on your production. So, we always have gap between working model on testset and real world applications.
#DataScience

https://twitter.com/jalilnkh/status/1585740724087259140?t=zr4zKR68MCRgGlAschy8cg&s=19