استفاده از مدل GPT-2 برای تولید متن بلاگ-پست فارسی توسط آقای افشین خاشعی از مدیران ارشد توسعه نرم افزار در Amazon:
مثال اول:
https://lnkd.in/gxvxvuT
مثال دوم:
https://lnkd.in/gxniKcT
مثال سوم:
https://lnkd.in/gyyJcTk
توضیحات فنی:
https://medium.com/@khashei/a-not-so-dangerous-ai-in-the-persian-language-39172a641c84
مثال اول:
https://lnkd.in/gxvxvuT
مثال دوم:
https://lnkd.in/gxniKcT
مثال سوم:
https://lnkd.in/gyyJcTk
توضیحات فنی:
https://medium.com/@khashei/a-not-so-dangerous-ai-in-the-persian-language-39172a641c84
Forwarded from Tensorflow(@CVision) (Vahid Reza Khazaie)
همونطور که میدونید اخیرا انتشار مدل زبانی GPT-3 سر و صدای زیادی به پا کرده. توی این ویدئو ازش برای یه کاربرد جالب مثل نوشتن کوئری استفاده شده...
https://twitter.com/FaraazNishtar/status/1285934622891667457?s=20
میتونید درباره این مدل بیشتر بخونید:
https://openai.com/blog/openai-api/
https://twitter.com/FaraazNishtar/status/1285934622891667457?s=20
میتونید درباره این مدل بیشتر بخونید:
https://openai.com/blog/openai-api/
Twitter
faraaz.eth 🦇🔊
I got GPT-3 to start writing my SQL queries for me p.s. these work against my *actual* database!
ALBERT-Persian: A Lite BERT for Self-supervised Learning of Language Representations for the Persian Language
Try:
https://albert-lab.m3hrdadfi.me/
GitHub:
https://github.com/m3hrdadfi/albert-persian#albert-persian-a-lite-bert-for-self-supervised-learning-of-language-representations-for-the-persian-language
Try:
https://albert-lab.m3hrdadfi.me/
GitHub:
https://github.com/m3hrdadfi/albert-persian#albert-persian-a-lite-bert-for-self-supervised-learning-of-language-representations-for-the-persian-language
GPU and TPU-accelerated NumPy API, interoperable with the rest of the TF ecosystem.
https://www.tensorflow.org/api_docs/python/tf/experimental/numpy
https://www.tensorflow.org/api_docs/python/tf/experimental/numpy
Face detection with TFLite in Flutter:
https://medium.com/@mundorap2010/face-detection-with-tflite-model-without-firebase-in-flutter-6eadf888f3b0
https://medium.com/@mundorap2010/face-detection-with-tflite-model-without-firebase-in-flutter-6eadf888f3b0
Medium
Face Detection with TFLite model (without Firebase) in Flutter
In this article, we will see how to detect faces using Tensorflow models without using libraries like Firebase in Flutter, the process is…
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handcalcs:
Python calculations in Jupyter,
as though you wrote them by hand.
$ 𝚙𝚒𝚙 𝚒𝚗𝚜𝚝𝚊𝚕𝚕 𝚑𝚊𝚗𝚍𝚌𝚊𝚕𝚌𝚜
GitHub:
https://github.com/connorferster/handcalcs
Python calculations in Jupyter,
as though you wrote them by hand.
$ 𝚙𝚒𝚙 𝚒𝚗𝚜𝚝𝚊𝚕𝚕 𝚑𝚊𝚗𝚍𝚌𝚊𝚕𝚌𝚜
GitHub:
https://github.com/connorferster/handcalcs
Forwarded from Tensorflow(@CVision) (Vahid Reza Khazaie)
هوشمندی فارغ از اینکه مصنوعی باشه یا عمومی، واقعا چیه و چطوری اندازهگیری میشه؟ از فرانسوا شوله، نویسنده کراس و از مهندسین گوگل، توی این پادکست بشنوید:
https://www.youtube.com/watch?v=PUAdj3w3wO4
https://www.youtube.com/watch?v=PUAdj3w3wO4
YouTube
François Chollet: Measures of Intelligence | Lex Fridman Podcast #120
François Chollet is an AI researcher at Google and creator of Keras. Support this podcast by supporting our sponsors (and get discount):
- Babbel: https://babbel.com and use code LEX
- MasterClass: https://masterclass.com/lex
- Cash App: download app & use…
- Babbel: https://babbel.com and use code LEX
- MasterClass: https://masterclass.com/lex
- Cash App: download app & use…
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Opacus, a new high-speed library for training PyTorch models with differential privacy (DP) that’s more scalable than existing state-of-the-art methods.
https://ai.facebook.com/blog/introducing-opacus-a-high-speed-library-for-training-pytorch-models-with-differential-privacy
https://blog.openmined.org/differentially-private-deep-learning-using-opacus-in-20-lines-of-code/amp/?__twitter_impression=true
https://ai.facebook.com/blog/introducing-opacus-a-high-speed-library-for-training-pytorch-models-with-differential-privacy
https://blog.openmined.org/differentially-private-deep-learning-using-opacus-in-20-lines-of-code/amp/?__twitter_impression=true
Data Science Tools study guides for MIT's 15.003
https://github.com/shervinea/mit-15-003-data-science-tools
https://github.com/shervinea/mit-15-003-data-science-tools
GitHub
GitHub - shervinea/mit-15-003-data-science-tools: Study guides for MIT's 15.003 Data Science Tools
Study guides for MIT's 15.003 Data Science Tools. Contribute to shervinea/mit-15-003-data-science-tools development by creating an account on GitHub.
Google Scanned Object: A dataset of common household objects that have been 3D scanned for use in robotic simulation and synthetic perception research.
https://app.ignitionrobotics.org/GoogleResearch/fuel/collections/Google%20Scanned%20Objects
https://app.ignitionrobotics.org/GoogleResearch/fuel/collections/Google%20Scanned%20Objects
How to Create a Cartoonizer Android app with TensorFlow Lite.
https://blog.tensorflow.org/2020/09/how-to-create-cartoonizer-with-tf-lite.html?linkId=99210557&m=1
https://blog.tensorflow.org/2020/09/how-to-create-cartoonizer-with-tf-lite.html?linkId=99210557&m=1
ارایه های چهارمین مدرسه پیشرفته هوش مصنوعی IPM:
https://www.youtube.com/playlist?list=PL0iwSr5ko6qZqRm8kHNZOV5Sl78qOBZap&feature=share
ارایه های پیشنهادی:
Capsule Networks - Sara Sabour
https://youtu.be/Zn1CUWW0v10?list=PL0iwSr5ko6qZqRm8kHNZOV5Sl78qOBZap
Probabilistic ML and AI - Zubin Ghahramani
https://youtu.be/dLf3FRR9BE0?list=PL0iwSr5ko6qZqRm8kHNZOV5Sl78qOBZap
Approximate DP and Batch learning - Amir-massoud Farahmand
https://youtu.be/YK7m2Gy3Pbo?list=PL0iwSr5ko6qZqRm8kHNZOV5Sl78qOBZap
Representation Learning without labels -Ali Eslami
https://youtu.be/rHNGRD20gtE?list=PL0iwSr5ko6qZqRm8kHNZOV5Sl78qOBZap
https://www.youtube.com/playlist?list=PL0iwSr5ko6qZqRm8kHNZOV5Sl78qOBZap&feature=share
ارایه های پیشنهادی:
Capsule Networks - Sara Sabour
https://youtu.be/Zn1CUWW0v10?list=PL0iwSr5ko6qZqRm8kHNZOV5Sl78qOBZap
Probabilistic ML and AI - Zubin Ghahramani
https://youtu.be/dLf3FRR9BE0?list=PL0iwSr5ko6qZqRm8kHNZOV5Sl78qOBZap
Approximate DP and Batch learning - Amir-massoud Farahmand
https://youtu.be/YK7m2Gy3Pbo?list=PL0iwSr5ko6qZqRm8kHNZOV5Sl78qOBZap
Representation Learning without labels -Ali Eslami
https://youtu.be/rHNGRD20gtE?list=PL0iwSr5ko6qZqRm8kHNZOV5Sl78qOBZap
YouTube
ASOC2020 - YouTube
OpenAI ‘GPT-f’ Delivers SOTA Performance in Automated Mathematical Theorem Proving
https://arxiv.org/pdf/2009.03393.pdf
https://arxiv.org/pdf/2009.03393.pdf
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Pixelopolis, a self-driving car demo from Google I/O built with TF-Lite
https://blog.tensorflow.org/2020/07/pixelopolis-self-driving-car-demo-tensorflow-lite.html
https://blog.tensorflow.org/2020/07/pixelopolis-self-driving-car-demo-tensorflow-lite.html
Array programming with NumPy
(NumPy paper after 25 years)
https://www.nature.com/articles/s41586-020-2649-2
(NumPy paper after 25 years)
https://www.nature.com/articles/s41586-020-2649-2
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RigL, a new algorithm for training sparse neural networks by Google.
Instead of pruning a pre-existing dense network, it dynamically builds one during training without sacrificing accuracy relative to traditional approaches.
https://ai.googleblog.com/2020/09/improving-sparse-training-with-rigl.html?m=1
Instead of pruning a pre-existing dense network, it dynamically builds one during training without sacrificing accuracy relative to traditional approaches.
https://ai.googleblog.com/2020/09/improving-sparse-training-with-rigl.html?m=1
Forwarded from Loop Academy | آکادمیِ لوپ
🧠 مجموعه کارگاه های یادگیری عمیق
- کارگاه مقدماتی شبکه های عصبی
- کارگاه شبکه های عصبی کانولوشنی (CNN)
- کارگاه شبمه های عصبی بازگشتی (RNN)
- کارگاه شبکه های عصبی اسپایکی (SNN)
📅 تاریخ برگزاری: از پنج شنبه 10 مهر تا جمعه 2 آبان ماه هر پنج شنبه و جمعه از ساعت 10 الی 17
🖥 این دوره به صورت آنلاین برگزار خواهد شد.
‼️با ثبت نام در مجموعه کارگاه های یادگیری عمیق از 120 هزار تومان تخفیف و 50 امتیاز کاربری برخوردار می شوید.
⭕️ برای مشاهده جزئیات بیشتر و ثبت نام روی این لینک کلیک کنید.
❌ دوره دارای ظرفیت محدود می باشد.
🕙 مدت این دوره: 36 ساعت
➖➖➖➖➖➖➖➖
@LoopAcademy
- کارگاه مقدماتی شبکه های عصبی
- کارگاه شبکه های عصبی کانولوشنی (CNN)
- کارگاه شبمه های عصبی بازگشتی (RNN)
- کارگاه شبکه های عصبی اسپایکی (SNN)
📅 تاریخ برگزاری: از پنج شنبه 10 مهر تا جمعه 2 آبان ماه هر پنج شنبه و جمعه از ساعت 10 الی 17
🖥 این دوره به صورت آنلاین برگزار خواهد شد.
‼️با ثبت نام در مجموعه کارگاه های یادگیری عمیق از 120 هزار تومان تخفیف و 50 امتیاز کاربری برخوردار می شوید.
⭕️ برای مشاهده جزئیات بیشتر و ثبت نام روی این لینک کلیک کنید.
❌ دوره دارای ظرفیت محدود می باشد.
🕙 مدت این دوره: 36 ساعت
➖➖➖➖➖➖➖➖
@LoopAcademy
👍1
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Datasets & modeling tools that are accessible to the public to help address the health & economic crisis against #COVID19.
https://blog.google/technology/health/making-data-useful-public-health/amp/
https://blog.google/technology/health/making-data-useful-public-health/amp/