Forwarded from Complex Systems Studies
⭕️ Fundamentals of Machine Learning
Lead instructor: Brendan Tracey and Artemy Kolchinsky
https://www.complexityexplorer.org/courses/81-fundamentals-of-machine-learning
About the Tutorial:
Machine Learning is a fast growing, rapidly advancing field that touches nearly everyone's lives. There has recently been an explosion of successful machine learning applications - in everything from voice recognition to to text analysis to deeper insights for researchers. While common and frequently talked about, most people have only a vague concept of how machine learning actually works.
In this tutorial, Dr. Artemy Kolchinsky and Dr. Brendan Tracey outline exactly what it is that makes machine learning so special in an accessible way. The principles of training and generalization in machine learning are explained with ample metaphors and visual intuitions, an extended analysis of machine learning in games provides a thorough example, and a closer look at the deep neural nets that are the core of successful machine learning. Finally it addresses when it's appropriate to use (and not use) machine learning in problem solving, as well as an example of scientific research incorporating machine learning principles.
Students of all levels should be able to follow this reasonably-paced introduction to one of the most important engineering breakthroughs of our time.
High quality videos:
🎞 https://www.aparat.com/video/video/listuser/username/carimi/usercat/110284
Lead instructor: Brendan Tracey and Artemy Kolchinsky
https://www.complexityexplorer.org/courses/81-fundamentals-of-machine-learning
About the Tutorial:
Machine Learning is a fast growing, rapidly advancing field that touches nearly everyone's lives. There has recently been an explosion of successful machine learning applications - in everything from voice recognition to to text analysis to deeper insights for researchers. While common and frequently talked about, most people have only a vague concept of how machine learning actually works.
In this tutorial, Dr. Artemy Kolchinsky and Dr. Brendan Tracey outline exactly what it is that makes machine learning so special in an accessible way. The principles of training and generalization in machine learning are explained with ample metaphors and visual intuitions, an extended analysis of machine learning in games provides a thorough example, and a closer look at the deep neural nets that are the core of successful machine learning. Finally it addresses when it's appropriate to use (and not use) machine learning in problem solving, as well as an example of scientific research incorporating machine learning principles.
Students of all levels should be able to follow this reasonably-paced introduction to one of the most important engineering breakthroughs of our time.
High quality videos:
🎞 https://www.aparat.com/video/video/listuser/username/carimi/usercat/110284
Complex Systems Studies
⭕️ Fundamentals of Machine Learning Lead instructor: Brendan Tracey and Artemy Kolchinsky https://www.complexityexplorer.org/courses/81-fundamentals-of-machine-learning About the Tutorial: Machine Learning is a fast growing, rapidly advancing field…
مبانی یادگیری ماشین هماکنون روی شبکه داخلی، قسمت کورسهای تحصیلات تکمیلی
https://www.complexityexplorer.org/courses/81-fundamentals-of-machine-learning
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
https://www.complexityexplorer.org/courses/81-fundamentals-of-machine-learning
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
کتابخانه دیجیتال خواجهنصیرالدینطوسی pinned «سلام به همه ⚡️ بهمنظور دسترسی راحتتر به فایلهای آموزشی حجیم مانند ویدیو سخنرانیها یا کورسهای آموزشی، امکانی فراهم شده تا با متصل شدن به شبکه داخلی دانشگاه (SBU) بتوانید با سرعت خوبی فایلهای مورد نظر را ببینید یا دانلود کنید. برای اینکار: 1⃣ به شبکه…»
ویدئو سمینار دکتر علیشاهیها با عنوان Holography and complexity بر روی شبکه داخلی قرار دارد.
Seminars & Talks => Weekly Seminars
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
Seminars & Talks => Weekly Seminars
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
Forwarded from انجمن علمی فیزیک بهشتی (SBU)
#سمینار_عمومی این هفته
Holography and complexity
-۳شنبه ۱۷ بهمن؛ ساعت ۱۶
-تالار ابن هیثم، دانشکده فیزیک
کانال انجمن علمی دانشجویی فیزیک
@sbu_physics
Holography and complexity
-۳شنبه ۱۷ بهمن؛ ساعت ۱۶
-تالار ابن هیثم، دانشکده فیزیک
کانال انجمن علمی دانشجویی فیزیک
@sbu_physics
این سمینار به روی شبکه داخلی قرار دارد. قسمت سخنرانیهای سیستمهای پیچیده.
Seminars & Talks => Complex Systems
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
Seminars & Talks => Complex Systems
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
دوره مقدماتی علوم اعصاب شناختی مناسب برای دانشجویان کارشناسی هماکنون بر روی شبکه داخلی دانشکده.
🔗 goo.gl/Q65AsR
(BS => 3rd & 4th Year)
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
🔗 goo.gl/Q65AsR
(BS => 3rd & 4th Year)
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
نسخه جدید اوبونتو هماکنون روی شبکه داخلی.
Others => OS
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
Others => OS
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
کتابخانه دیجیتال خواجهنصیرالدینطوسی
نسخه جدید اوبونتو هماکنون روی شبکه داخلی. Others => OS ⚡️ 192.168.80.180:8080 Username: physics Password: quantum
این نسخه اوبونتو از سری LTS است که ۵ سال ساپورت کامل میشن. یعنی شما با نصب این سیستم عامل میتونین تا ۲۰۲۳ از ساپورت کامل و آپدیت شدن و پچ شدن مشکلات امنیتی و غیره مطمئن باشین. برای دانلود میتونین به سایت رسمی اوبونتو مراجعه کنین و برای آپگرید از Software & Updates شروع کنین.
مهتمرین تغییرات در سگ آب بایونیک، استفاده از کرنل ۴.۱۵ و استفاده از X برای محیط گرافیکی. ویلند هنوز راه زیادی داره و حدس زده می شه از ورژن ۲۰.۰۴ فعال بشه. گنوم روی ورژن ۳.۲۸ است و لیبره آفیس روی ورژن ۶.
نکته مهم دیگه اینه که اوبونتو ۳۲ بیتی دسکتاپ دیگه عرضه نمیشه چون تقریبا همه کامپیوترهای ماروزی ما ۶۴ بیتی هستن. از اونطرف gdm جایگزین lightdm شده و روی ویرچوال دسکتاپ ۱ کار می کنه که از هر دوی این تغییرات خوشحالم. با اینکه چیزهای ریزی هستن.
https://jadi.net
مهتمرین تغییرات در سگ آب بایونیک، استفاده از کرنل ۴.۱۵ و استفاده از X برای محیط گرافیکی. ویلند هنوز راه زیادی داره و حدس زده می شه از ورژن ۲۰.۰۴ فعال بشه. گنوم روی ورژن ۳.۲۸ است و لیبره آفیس روی ورژن ۶.
نکته مهم دیگه اینه که اوبونتو ۳۲ بیتی دسکتاپ دیگه عرضه نمیشه چون تقریبا همه کامپیوترهای ماروزی ما ۶۴ بیتی هستن. از اونطرف gdm جایگزین lightdm شده و روی ویرچوال دسکتاپ ۱ کار می کنه که از هر دوی این تغییرات خوشحالم. با اینکه چیزهای ریزی هستن.
https://jadi.net
ویدیو این ارائه هماکنون بر روی شبکه داخلی قابل دسترس است:
Seminars & Talks => Wikipedia
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
Seminars & Talks => Wikipedia
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
Scale-free networks are rare
Aaron Clauset
http://bit.ly/2NypVMh
Seminars & Talks => Complex Systems
192.168.80.180:8080
Username: physics
Password: quantum
Aaron Clauset
http://bit.ly/2NypVMh
Seminars & Talks => Complex Systems
192.168.80.180:8080
Username: physics
Password: quantum
Forwarded from Complex Systems Studies
🔖 Scale-free networks are rare
Anna D. Broido, Aaron Clauset
🔗 arxiv.org/pdf/1801.03400.pdf
📌 ABSTRACT
A central claim in modern network science is that real-world networks are typically "scale free," meaning that the fraction of nodes with degree k follows a power law, decaying like k−α, often with 2<α<3. However, empirical evidence for this belief derives from a relatively small number of real-world networks. We test the universality of scale-free structure by applying state-of-the-art statistical tools to a large corpus of nearly 1000 network data sets drawn from social, biological, technological, and informational sources. We fit the power-law model to each degree distribution, test its statistical plausibility, and compare it via a likelihood ratio test to alternative, non-scale-free models, e.g., the log-normal. Across domains, we find that scale-free networks are rare, with only 4% exhibiting the strongest-possible evidence of scale-free structure and 52% exhibiting the weakest-possible evidence. Furthermore, evidence of scale-free structure is not uniformly distributed across sources: social networks are at best weakly scale free, while a handful of technological and biological networks can be called strongly scale free. These results undermine the universality of scale-free networks and reveal that real-world networks exhibit a rich structural diversity that will likely require new ideas and mechanisms to explain.
Anna D. Broido, Aaron Clauset
🔗 arxiv.org/pdf/1801.03400.pdf
📌 ABSTRACT
A central claim in modern network science is that real-world networks are typically "scale free," meaning that the fraction of nodes with degree k follows a power law, decaying like k−α, often with 2<α<3. However, empirical evidence for this belief derives from a relatively small number of real-world networks. We test the universality of scale-free structure by applying state-of-the-art statistical tools to a large corpus of nearly 1000 network data sets drawn from social, biological, technological, and informational sources. We fit the power-law model to each degree distribution, test its statistical plausibility, and compare it via a likelihood ratio test to alternative, non-scale-free models, e.g., the log-normal. Across domains, we find that scale-free networks are rare, with only 4% exhibiting the strongest-possible evidence of scale-free structure and 52% exhibiting the weakest-possible evidence. Furthermore, evidence of scale-free structure is not uniformly distributed across sources: social networks are at best weakly scale free, while a handful of technological and biological networks can be called strongly scale free. These results undermine the universality of scale-free networks and reveal that real-world networks exhibit a rich structural diversity that will likely require new ideas and mechanisms to explain.
ادوارد ویتن درسگفتاری روی نظریه اطلاعات گفته که ویدیوش روی شبکه داخلی موجوده:
Seminars & Talks => Complex Systems
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
Seminars & Talks => Complex Systems
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
Forwarded from Complex Systems Studies
🔖 A Mini-Introduction To Information Theory
🙋🏻♂ Edward Witten
🔗 https://arxiv.org/pdf/1805.11965
📌 ABSTRACT
This article consists of a very short introduction to classical and quantum information theory. Basic properties of the classical Shannon entropy and the quantum von Neumann entropy are described, along with related concepts such as classical and quantum relative entropy, conditional entropy, and mutual information. A few more detailed topics are considered in the quantum case.
🙋🏻♂ Edward Witten
🔗 https://arxiv.org/pdf/1805.11965
📌 ABSTRACT
This article consists of a very short introduction to classical and quantum information theory. Basic properties of the classical Shannon entropy and the quantum von Neumann entropy are described, along with related concepts such as classical and quantum relative entropy, conditional entropy, and mutual information. A few more detailed topics are considered in the quantum case.
هر دوی ویدیوها روی شبکه داخلی قرار دارند:
Seminars & Talks => Complex Systems
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
Seminars & Talks => Complex Systems
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
هماکنون روی شبکه داخلی قرار دارد.
https://www.udemy.com/python-for-data-science-and-machine-learning-bootcamp/
Graduate
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum
https://www.udemy.com/python-for-data-science-and-machine-learning-bootcamp/
Graduate
⚡️ 192.168.80.180:8080
Username: physics
Password: quantum