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.)You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session. Dismiss alert
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
Machine Learning (Theory) – Machine learning and learning theory research
(Dylan Foster and Alex Lamb both helped in creating this.) In thinking about what are good research problems, it’s sometimes helpful to switch from what is understood to what is clearly possible. This encourages us to think beyond simply improving the existing system. For example, we have seen instances throughout the history of machine learning where researchers have argued for fixing an architec
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Elements of Statistical Learning: data mining, inference, and prediction. 2nd Edition.
Semi-supervised Learning
パターン認識・画像処理手法の解説＠栗田多喜夫先生
Amazon.co.jp: Machine Learning: An Algorithmic Perspective (Chapman & Hall/CRC Machine Learning & Pattern Recognition): Marsland, Stephen: 本
