Deep Learningでラブライブ！キャラを識別する - christinaの備忘録
このところDeep Learningが相当流行っているようで、ほとんど至るところで話題になっているのを見ます。 Deep Learningは深層学習とも呼ばれ、ニューラルネットワークの層をこれまでより深くして機械学習を行う技法です（だそうです）。 画像認識コンテストで他の方法と比べて非常に高い精度を示しており、以前は人の手で行っていた特徴の抽出まで行えます。 以前であれば車を認識するには車はどのような特徴を持っているかを人がモデル化して入力していたわけですが、この特徴を入力画像と与えられたラベルからニューラルネットワークが捉えてくれます。詳しいことはDeep Learningで検索して出てくる記事やスライドを参照のこと。 Deep Learning自体は容易に実装可能なものではなさそうですが、多くの研究グループがDeep Learningを行うためのソフトウェアをオープンソースにしているた
Zinnia: 機械学習ベースのポータブルな手書き文字認識エンジン
Zinnia: 機械学習ベースのポータブルなオンライン手書き文字認識エンジン [日本語][英語] Zinniaは機械学習アルゴリズム SVM を用いたポータブルで汎用的な オンライン手書き文字認識エンジンです。Zinniaは組み込みの容易さと汎用性を高めるために、 文字のレンダリング機能は持っていません。Zinniaは文字のストローク情報を座標の連続として受け取り、 確からしい順にスコア付きでN文字の認識結果を返すだけに機能を限定しています。 また、認識エンジンは完全に機械学習ベースであるために、文字のみならずユーザの任意のマウス・ペンストロークに対して任意の文字列をマッピングするような認識エンジンを小コスト作成することができます。 主な特徴 機械学習アルゴリズムSVMによる高い認識精度 ポータブルでコンパクトな設計 -- POSIX/Windows (C++ STLのみに依存) リエント
Good Freely Available Textbooks on Machine Learning - MetaOptimize Q+A
I'm starting this question to collect a list of good freely available textbooks that concentrate on some aspect of machine learning (rather than applications of ML -- these can go in separate questions). Good tutorials could be included as well, but I'd rather not have, say, slides that are a bit cryptic on their own. The Elements of Statistical Machine Learning is a great text covering most core
Patterns for Research in Machine Learning | Ali Eslami
18 Jul 2012 Here I list a handful of code patterns that I wish I was more aware of when I started my PhD. Each on its own may seem pointless, but collectively they go a long way towards making the typical research workflow more efficient. And an efficient workflow makes it just that little bit easier to ask the research questions that matter. My guess is that these patterns will not only be useful
SKILLPUNCH
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ImageNet
ImageNet Large Scale Visual Recognition Challenge 2010 (ILSVRC2010) Registration Download Introduction Data Task Development kit Timetable Features Submission Citationnew Organizers Contact News September 2, 2014: A new paper which describes the collection of the ImageNet Large Scale Visual Recognition Challenge dataset, analyzes the results of the past five years of the challenge, and even compar
Top 10 Free Educational Tools - Top 10 Free Educational Tools - My Top Ten Australia
Courtesy of Teacher Challenge by Edublogs 10 - Wordle Most people that write for the web tell us that a picture helps to draw reader interest to the post. What if the picture is composed from words? Does it have the same impact? Wordle, or a word cloud, helps to interpret the meaning of the words by assigning font size according to how frequently the word appears in the targeted text. This is one
Learn a Language | Free Online Language Learning
Learn a Language Learn a language right here with hundreds of free language-learning lessons, games and activities. Join us and have some fun. Start learning now Learn a Language Learn a language right here with hundreds of free language-learning lessons, games and activities. Join us and have some fun.
Machine Learning (Theory) – Machine learning and learning theory research
The stark success of OpenAI’s GPT4 model surprised me shifting my view from “really good autocomplete” (roughly inline with intuitions here) to a dialog agent exhibiting a significant scope of reasoning and intelligence. Some of the MSR folks did a fairly thorough study of capabilities which seems like a good reference. I think of GPT4 as an artificial savant: super-John capable in some language-c
Learning to Rank Challenge
March 1st 2010: Competition begins May 31st 2010: Competition ends June 2010: Winners announced June 25th 2010: LTRC workshop at ICML conference Haifa, Israel Benchmark your LTR algorithm against the best in industry Though over 100 papers have been published in the learning to rank (LTR) field, most of the large-scale, real-world datasets are not publicly available. This makes drawing comparisons
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【作業用BGM】超かっこいい洋楽ロック！テンションあがる！！
https://www.nins.jp/public_information/pdf/colloquium/2nd_17_b2_bunkakai_s.pdf
GitHub - dive-into-machine-learning/dive-into-machine-learning: Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)
http://www.iro.umontreal.ca/~bengioy/DLbook/
CS 194-10, Fall 2011
Quizlet
RLAI open page
Elements of Statistical Learning: data mining, inference, and prediction. 2nd Edition.
Semi-supervised Learning
Learning English - 6 Minute English - Mr Smith or John?