دیتاستی از توییتهای جو بایدن از ۲۰۰۷ تا ۲۰۲۰:
https://www.kaggle.com/rohanrao/joe-biden-tweets/tasks?taskId=2527&utm_medium=social&utm_source=twitter.com&utm_campaign=task+published
#دیتاست #دیتا
#dataset
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python
https://www.kaggle.com/rohanrao/joe-biden-tweets/tasks?taskId=2527&utm_medium=social&utm_source=twitter.com&utm_campaign=task+published
#دیتاست #دیتا
#dataset
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python
Kaggle
Joe Biden Tweets (2007 - 2020)
Tweets of Joe Biden's official Twitter handle @JoeBiden
https://twitter.com/particular6/status/1320596248978665472?s=20
PhD Position in Computer Science Project on Graph Based Methods for Pattern Recognition and Machine Learning The ideal candidate: Has a strong interest and background in pattern recognition and graph based representation Has excellent programming skills (in particular Python and/or Java) Has excellent writing and presentation skills Interested? For further information please contact the PhD supervisor: kaspar.riesen@inf.unibe.ch The applicant should submit a CV (including contacts of two referees) and a one-page motivation letter, highlighting her/his experiences in the above-mentioned points and indicating his/her motivation to join the project. Please send your application electronically to: kaspar.riesen@inf.unibe.ch
#موقعیت_تحصیلی #اپلای
#PhD_opportunities
PhD Position in Computer Science Project on Graph Based Methods for Pattern Recognition and Machine Learning The ideal candidate: Has a strong interest and background in pattern recognition and graph based representation Has excellent programming skills (in particular Python and/or Java) Has excellent writing and presentation skills Interested? For further information please contact the PhD supervisor: kaspar.riesen@inf.unibe.ch The applicant should submit a CV (including contacts of two referees) and a one-page motivation letter, highlighting her/his experiences in the above-mentioned points and indicating his/her motivation to join the project. Please send your application electronically to: kaspar.riesen@inf.unibe.ch
#موقعیت_تحصیلی #اپلای
#PhD_opportunities
Forwarded from old fashioned (Amir)
✔️ مستند The Age of A.I. 2019 توسط شبکه یوتیوب و در چند قسمت آماده شده است که و میزبانی آن را هم رابرت داونی جونیور ستاره سرشناس هالیوودی برعهده خواهد داشت. در این سری راهکارهای جذاب هوش مصنوعی و یادگیری ماشین بررسی شده و خواهیم دید که تکنولوژی با چه سرعتی در عصر حاضر در حال پیشرفت است.
🔗 لینک دانلود مستند همراه با زیرنویس فارسی
@ai_python
@oldfashioned7
🔗 لینک دانلود مستند همراه با زیرنویس فارسی
@ai_python
@oldfashioned7
هزینه های تبلیغاتی که انجام شده صرف خرید یک بخاری برای یکی ازهموطنانمون بوده در این روزهای سخت باهمهمراه باشیم
DLeX: AI Python
هزینه های تبلیغاتی که انجام شده صرف خرید یک بخاری برای یکی ازهموطنانمون بوده در این روزهای سخت باهمهمراه باشیم
من فرزاد و همه ادمینهای کانال خیلی خوشحالیم که اشتراک شما در کانال تونست ما رو به اینجا برسونه که تو روزهای سرد بتونیم کمک حال هموطنمون باشیم.
بدون حضور شما دوستان این ممکن نبود.
ماهم میدونیم که تبلیغ از کیفیت کانال کم میکنه ولی همین تبلیغها مبالغی هرچند ناچیز جمع میکنند که میشه باهاش بذر مهربونی کاشت.
به نوبه خودم از همتون ممنونم :)
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python
بدون حضور شما دوستان این ممکن نبود.
ماهم میدونیم که تبلیغ از کیفیت کانال کم میکنه ولی همین تبلیغها مبالغی هرچند ناچیز جمع میکنند که میشه باهاش بذر مهربونی کاشت.
به نوبه خودم از همتون ممنونم :)
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python
By explaining a model's decisions, we can cover gaps in our understanding of the problem - its incompleteness.
#DataScience #ArtificialIntelligence #MachineLearning
https://hubs.li/H0yRBFJ0
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_En
#DataScience #ArtificialIntelligence #MachineLearning
https://hubs.li/H0yRBFJ0
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_En
Open Data Science - Your News Source for AI, Machine Learning & more
Dealing with the Incompleteness of Machine Learning
By explaining a machine learning model's decisions, we can cover gaps in our understanding of the problem - it's incompleteness.
پیکره Common Crawl که اکثر ترنسفرمرها بر پایه آن ترین شده اند:
CC-100: Monolingual Datasets from Web Crawl Data:
http://data.statmt.org/cc-100/
این داده بر بیش از صد زبان دنیا ارایه شده است و مجموعه بسیار ارزشمندی در حوزه پردازش زبان طبیعی می باشد.
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_En
CC-100: Monolingual Datasets from Web Crawl Data:
http://data.statmt.org/cc-100/
این داده بر بیش از صد زبان دنیا ارایه شده است و مجموعه بسیار ارزشمندی در حوزه پردازش زبان طبیعی می باشد.
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_En
Training Generative Adversarial Networks by Solving Ordinary Differential Equations
pdf:
https://arxiv.org/pdf/2010.15040.pdf
abs: https://arxiv.org/abs/2010.15040
github:
https://github.com/deepmind/deepmind-research/tree/master/
#مقاله
❇️ @AI_Python
🗣 @AI_Python_arXiv
❇️ @AI_Python_En
pdf:
https://arxiv.org/pdf/2010.15040.pdf
abs: https://arxiv.org/abs/2010.15040
github:
https://github.com/deepmind/deepmind-research/tree/master/
#مقاله
❇️ @AI_Python
🗣 @AI_Python_arXiv
❇️ @AI_Python_En
Forwarded from DLeX: AI Python (Deleted Account)
16 منبع آموزشی الگوریتمهای هوش مصنوعی〰️〰️〰️
♾ 1. Speech and Language Processing by Dan Jurafsky and James Martin
🔊 2. Deep Learning for Natural Language Processing by Richard Socher (Stanford University)
🔔 3. Natural Language Processing (NLP) by Microsoft
🔸 4. Andrew Ng’s course on Machine Learning
🔸 5. The video lectures and resources for Stanford’s Natural Language Processing with Deep Learning
🔰 Part 2
🔹6. Sequence Models for Time Series and Natural Language Processing
🔺 7. Deep Natural Language Processing course offered in Hilary Term 2017 at the University of Oxford.
🔺 8. Natural Language Processing Fundamentals in Python by Datacamp
🔺 9 Natural Language Processing by Higher School of Economics
🔸 10 How to Build a Chatbot Without Coding by IBM
🔸 11. CS 388: Natural Language Processing by University of Texas
🔸 12. Natural Language Processing with Python
⚡️ 13. CSEP 517: Natural Language Processing by University of Washington
🔰 14. Dan Jurafsky & Chris Manning: Natural Language Processing
📘 15. NATURAL LANGUAGE PROCESSING by Carnegie Mellon University
📘 16. CS224n: Natural Language Processing with Deep Learning by Stanford University
#منابع #یادگیری_ماشین #فیلم #کلاس_آموزشی #الگوریتمها #پردازش_زبان_طبیعی #هوش_مصنوعی #یادگیری_عمیق
join👇👇👇
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
♾ 1. Speech and Language Processing by Dan Jurafsky and James Martin
🔊 2. Deep Learning for Natural Language Processing by Richard Socher (Stanford University)
🔔 3. Natural Language Processing (NLP) by Microsoft
🔸 4. Andrew Ng’s course on Machine Learning
🔸 5. The video lectures and resources for Stanford’s Natural Language Processing with Deep Learning
🔰 Part 2
🔹6. Sequence Models for Time Series and Natural Language Processing
🔺 7. Deep Natural Language Processing course offered in Hilary Term 2017 at the University of Oxford.
🔺 8. Natural Language Processing Fundamentals in Python by Datacamp
🔺 9 Natural Language Processing by Higher School of Economics
🔸 10 How to Build a Chatbot Without Coding by IBM
🔸 11. CS 388: Natural Language Processing by University of Texas
🔸 12. Natural Language Processing with Python
⚡️ 13. CSEP 517: Natural Language Processing by University of Washington
🔰 14. Dan Jurafsky & Chris Manning: Natural Language Processing
📘 15. NATURAL LANGUAGE PROCESSING by Carnegie Mellon University
📘 16. CS224n: Natural Language Processing with Deep Learning by Stanford University
#منابع #یادگیری_ماشین #فیلم #کلاس_آموزشی #الگوریتمها #پردازش_زبان_طبیعی #هوش_مصنوعی #یادگیری_عمیق
join👇👇👇
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
Forwarded from DLeX: AI Python (Farzad 🦅)
آموزش دوره سایت کورسرا
Introduction to Deep Learning and Neural Networks with Keras
♦️ 1- Introduction to Deep Learning
♦️ 2 Neurons and Neural Networks
♦️ 3 Artificial Neural Networks
♦️ 4 Gradient Descent
♦️ 5 Backpropagation
♦️ 6 Vanishing Gradient
🔉 7 Activation Functions
🔉 8 Deep Learning Libraries
🔉 9 Regression Models with Keras
🔉 10 Classification Models with Keras
🔉 11 Shallow Versus Deep Neural Networks
🔸 12 Convolutional Neural Networks
🔸 13 Recurrent Neural Networks
🔸 14 Autoencoders
🔸 15 Summary
#فیلم #یادگیری_عمیق #منابع #شبکه_عصبی #کلاس_آموزشی #پایتون #کورسرا
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
Introduction to Deep Learning and Neural Networks with Keras
♦️ 1- Introduction to Deep Learning
♦️ 2 Neurons and Neural Networks
♦️ 3 Artificial Neural Networks
♦️ 4 Gradient Descent
♦️ 5 Backpropagation
♦️ 6 Vanishing Gradient
🔉 7 Activation Functions
🔉 8 Deep Learning Libraries
🔉 9 Regression Models with Keras
🔉 10 Classification Models with Keras
🔉 11 Shallow Versus Deep Neural Networks
🔸 12 Convolutional Neural Networks
🔸 13 Recurrent Neural Networks
🔸 14 Autoencoders
🔸 15 Summary
#فیلم #یادگیری_عمیق #منابع #شبکه_عصبی #کلاس_آموزشی #پایتون #کورسرا
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
#استخدام در استارت اپ DataKnow از زیرمجموعه های دیجیکلا نکست فرصتی خوبی برای شروع است
Forwarded from DLeX: AI Python (Farzad 🦅)
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LSTM is dead. Long Live Transformers!
How LSTM models for Natural Language Processing (NLP) have been practically replaced by transformer-based models. Basic background on NLP, and a brief history of supervised learning techniques on documents, from bag of words, through vanilla RNNs and LSTM. Then there's a technical deep dive into how Transformers work with multi-headed self-attention, and positional encoding. Includes sample code for applying these ideas to real-world projects.
#کنفرانس #فیلم #منابع #پردازش_زبان_طبیعی #الگوریتمها #یادگیری_عمیق
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
How LSTM models for Natural Language Processing (NLP) have been practically replaced by transformer-based models. Basic background on NLP, and a brief history of supervised learning techniques on documents, from bag of words, through vanilla RNNs and LSTM. Then there's a technical deep dive into how Transformers work with multi-headed self-attention, and positional encoding. Includes sample code for applying these ideas to real-world projects.
#کنفرانس #فیلم #منابع #پردازش_زبان_طبیعی #الگوریتمها #یادگیری_عمیق
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
Media is too big
VIEW IN TELEGRAM
Machine Learning with Python
14 Logistic Regression Training
#یادگیری_ماشین #کلاس_آموزشی #منابع #فیلم #کورسرا #پایتون
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python
14 Logistic Regression Training
#یادگیری_ماشین #کلاس_آموزشی #منابع #فیلم #کورسرا #پایتون
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python
Forwarded from DLeX: AI Python (Farzad 🦅)
آموزش دوره سایت کورسرا
Introduction to Deep Learning and Neural Networks with Keras
♦️ 1- Introduction to Deep Learning
♦️ 2 Neurons and Neural Networks
♦️ 3 Artificial Neural Networks
♦️ 4 Gradient Descent
♦️ 5 Backpropagation
♦️ 6 Vanishing Gradient
🔉 7 Activation Functions
🔉 8 Deep Learning Libraries
🔉 9 Regression Models with Keras
🔉 10 Classification Models with Keras
🔉 11 Shallow Versus Deep Neural Networks
🔸 12 Convolutional Neural Networks
🔸 13 Recurrent Neural Networks
🔸 14 Autoencoders
🔸 15 Summary
#فیلم #یادگیری_عمیق #منابع #شبکه_عصبی #کلاس_آموزشی #پایتون #کورسرا
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
Introduction to Deep Learning and Neural Networks with Keras
♦️ 1- Introduction to Deep Learning
♦️ 2 Neurons and Neural Networks
♦️ 3 Artificial Neural Networks
♦️ 4 Gradient Descent
♦️ 5 Backpropagation
♦️ 6 Vanishing Gradient
🔉 7 Activation Functions
🔉 8 Deep Learning Libraries
🔉 9 Regression Models with Keras
🔉 10 Classification Models with Keras
🔉 11 Shallow Versus Deep Neural Networks
🔸 12 Convolutional Neural Networks
🔸 13 Recurrent Neural Networks
🔸 14 Autoencoders
🔸 15 Summary
#فیلم #یادگیری_عمیق #منابع #شبکه_عصبی #کلاس_آموزشی #پایتون #کورسرا
❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
Forwarded from DLeX: AI Python (Farzad 🦅)
#منابع #کلاس_آموزشی
دورهی deep learning دانشگاه NYU که توسط اساتید بزرگی نظیر 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/
دورهی deep learning دانشگاه NYU که توسط اساتید بزرگی نظیر 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/