دانلود کورس های آموزشی دانشگاه استنفورد (مرتبط با هوش مصنوعی)

negin17h

مدیر تالارهای مهندسی کامپیوتر و رباتیکمتخصص #C
مدیر تالار
با سلام
در این تاپیک، لینک های دانلود کورس های آموزشی دانشگاه استنفورد را قرار خواهیم داد :gol:

هرگونه پست نامرتبط و یا اسپم بدون اطلاع قبلی حذف خواهد گردید :gol:
 

negin17h

مدیر تالارهای مهندسی کامپیوتر و رباتیکمتخصص #C
مدیر تالار
Stanford University : Artificial Intelligence

Stanford University : Artificial Intelligence

Stanford University : Artificial Intelligence

Title: Stanford University – CS221 : Artificial Intelligence
Video Format: MP4
File Size: 4.42 GB

More info

The Artificial Intelligence Graduate Certificate presents a solid foundation in the principles and technologies that underlie many facets of AI, including logic, knowledge representation, probabilistic models, and machine learning. Additionally, students have the option to pursue particular topics in more depth, with coursework available in areas such as robotics, vision, natural language processing or machine learning. A background in such areas is useful to a variety of practitioners including those that work in data mining, mathematical modeling, text understanding, and/or robotics.
  • Learn logic and reasoning methods from a computational perspective
  • Learn about agent, search, probabilistic models, perception and cognition, and machine learning

Download Links :

[Secureupload]
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negin17h

مدیر تالارهای مهندسی کامپیوتر و رباتیکمتخصص #C
مدیر تالار
Coursera – Machine Learning (Stanford) Spring 2013

Coursera – Machine Learning (Stanford) Spring 2013

Coursera – Machine Learning (Stanford) Spring 2013

Coursera – Machine Learning (Stanford) Spring 2013
Video Format: MP4
File Size: 1.48 GB



About the Course
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you’ll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you’ll learn about some of Silicon Valley’s best practices in innovation as it pertains to machine learning and AI.
This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you’ll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.

Download Links :

Uploaded :
http://uploaded.net/file/pwhi64fj/Coursera_MachineLearning(Stanford)_Spring2013.part1.rar
 
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