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先日ã€ã‚ªãƒ³ãƒ©ã‚¤ãƒ³å¦ç¿’サイトCourseraã®æ©Ÿæ¢°å¦ç¿’コース "Machine Learning by Stanford University" を修了ã—ã¾ã—ãŸã€‚ Machine Learning - Stanford University | Coursera (æ„Ÿå‹•ã®ã‚¨ãƒ³ãƒ‡ã‚£ãƒ³ã‚°å‹•ç”») ãŸã ã€æ©Ÿæ¢°å¦ç¿’ã«èˆˆå‘³ãŒã‚ã£ã¦æƒ…å ±åŽé›†ã‚’始ã‚ã¦ã‚‹äººã«ã¨ã£ã¦ã€ã€ŒCourseraã®æ©Ÿæ¢°å¦ç¿’コースãŒãŠã™ã™ã‚ã§ã™ã‚ˆã€ã¨ã„ã†è©±ã¯ 「ã¯ã„ã€çŸ¥ã£ã¦ã¾ã™ã€ ã¨ã„ã†æ„Ÿã˜ã§ã¯ãªã„ã§ã—ょã†ã‹ã€‚ 僕もãã‚“ãªæ„Ÿã˜ã§ã€å¹¾åº¦ã¨ãªã人や記事ã«åŒã‚³ãƒ¼ã‚¹ã‚’è–¦ã‚られãŸã‚Šã—ã¤ã¤ã€ãŸã¶ã‚“2å¹´ãらã„スルーã—続ã‘ã¦ããŸã¨æ€ã„ã¾ã™ã€‚ ã—ã‹ã—ç´„2ヶ月å‰ã€ã²ã‚‡ã‚“ãªãã£ã‹ã‘ã‹ã‚‰æœ¬è¬›åº§ã‚’始ã‚ã¦ã¿ã¦ã€ã‚„ã¯ã‚Šè©•åˆ¤é€šã‚Šæœ€é«˜ã ã£ãŸã¨æ€ã†ã¨åŒæ™‚ã«ã€åƒ•ã¨åŒã˜ã‚ˆã†ãªæ„Ÿã˜ã§ã“ã®ã‚³ãƒ¼ã‚¹ãŒè‰¯ã„らã—ã„ã¨çŸ¥ã‚ŠãªãŒã‚‰ã‚‚スルーã—続ã‘ã¦ã‚‹äººã¯å¤šã„ã‚“ã˜ã‚ƒãªã„ã‹ã¨æ€ã„ã¾ã—ã¦ã€ï¼ˆãŠã›ã£ã‹ã„ãª
Stanford University: Tensorflow for Deep Learning Research
No class on Friday, Feb 2. See syllabus. For the last year's website, visit here TensorFlow is a powerful open-source software library for machine learning developed by researchers at Google. It has many pre-built functions to ease the task of building different neural networks. TensorFlow allows distribution of computation across different computers, as well as multiple CPUs and GPUs within a sin
The Stanford Natural Language Processing Group
About A natural language parser is a program that works out the grammatical structure of sentences, for instance, which groups of words go together (as "phrases") and which words are the subject or object of a verb. Probabilistic parsers use knowledge of language gained from hand-parsed sentences to try to produce the most likely analysis of new sentences. These statistical parsers still make some
The Stanford Natural Language Processing Group
Overview Deep learning has recently shown much promise for NLP applications. Traditionally, in most NLP approaches, documents or sentences are represented by a sparse bag-of-words representation. There is now a lot of work, including at Stanford, which goes beyond this by adopting a distributed representation of words, by constructing a so-called "neural embedding" or vector space representation o
Stanford University CS224d: Deep Learning for Natural Language Processing
Please see cs224n.stanford.edu for the current (Winter 2017) version of this class. Natural language processing (NLP) is one of the most important technologies of the information age. Understanding complex language utterances is also a crucial part of artificial intelligence. Applications of NLP are everywhere because people communicate most everything in language: web search, advertisement, email
The Stanford Natural Language Processing Group
About Stanford CoreNLP provides a set of natural language analysis tools which can take raw text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, and mark up the structure of sentences in terms of phrases and word dependencies, indicate which noun phrases refer to the same entities, ind
Stanford University CS224d: Deep Learning for Natural Language Processing
Schedule and Syllabus Unless otherwise specified the course lectures and meeting times are: Tuesday, Thursday 3:00-4:20 Location: Gates B1
Stanford University CS224d: Deep Learning for Natural Language Processing
Please see cs224n.stanford.edu for the current (Winter 2017) version of this class. Natural language processing (NLP) is one of the most important technologies of the information age. Understanding complex language utterances is also a crucial part of artificial intelligence. Applications of NLP are everywhere because people communicate most everything in language: web search, advertisement, email
STANFORD COURSES ON THE LAGUNITA LEARNING PLATFORM | Stanford Online
About the Lagunita Platform Stanford released the first open source version of the edX platform, Open edX, in June 2013. We named our instance of the Open edX platform Lagunita, after the name of a cherished lake bed on the Stanford campus, a favorite gathering place of students. Stanford Online used Open edX technology to offer more than 200 free and open online courses on the Lagunita platform t
Unsupervised Feature Learning and Deep Learning Tutorial
Description: This tutorial will teach you the main ideas of Unsupervised Feature Learning and Deep Learning. By working through it, you will also get to implement several feature learning/deep learning algorithms, get to see them work for yourself, and learn how to apply/adapt these ideas to new problems. This tutorial assumes a basic knowledge of machine learning (specifically, familiarity with t
Deep Visual-Semantic Alignments for Generating Image Descriptions
Deep Visual-Semantic Alignments for Generating Image Descriptions We present a model that generates natural language descriptions of images and their regions. Our approach leverages datasets of images and their sentence descriptions to learn about the inter-modal correspondences between language and visual data. Our alignment model is based on a novel combination of Convolutional Neural Networks o
Deep Visual-Semantic Alignments for Generating Image Descriptions
Deep Visual-Semantic Alignments for Generating Image Descriptions We present a model that generates natural language descriptions of images and their regions. Our approach leverages datasets of images and their sentence descriptions to learn about the inter-modal correspondences between language and visual data. Our alignment model is based on a novel combination of Convolutional Neural Networks o
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https://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture15.pdf
Stanford University: Tensorflow for Deep Learning Research
https://web.stanford.edu/~cpiech/bio/papers/deepKnowledgeTracing.pdf
Stanford University CS231n: Deep Learning for Computer Vision
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http://ai.stanford.edu/~nilsson/QAI/qai.pdf
NIPS 2014 Accepted Papers
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