Arthur Samuel: Pioneer in Machine Learning

The PageRank citation ranking: Bringing order to the Web


Amazon.com recommendations: Item-to-team collaborative thinking

Matrix factorization techniques for recommender systems

The AI behind Watson: The technical article

Learning to drive: Perception for autonomous cars

Monocular pedestrian detection: Survey and experiments


Scientists See Promise in Deep-Learning Programs

Microsoft Research Shows a Promising New Breakthrough in Speech Translation Technology

2011 competition results

Building high-level features using large scale unsupervised learning

Multi-digit number recognition from street view imagery using deep convolutional neural networks


Learning fine-grained image similarity with deep ranking

Recursive deep models for semantic compositionality over a sentiment treebank

Multi-column deep neural networks for offline handwritten Chinese character classification


Generating sequences with recurrent neural networks

Deep visual-semantic alignments for generating image descriptions

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

Systematic analysis of breast cancer morphology uncovers stromal features associated with survival

Mitosis detection in breast cancer histology images with deep neural networks


Candidate sampling for neuron reconstruction from anisotropic electron microscopy volumes

Health systems leapfrogging in emerging economies

Was passiert, wenn wir einem Computer beibringen, wie man lernt? Der Technologe Jeremy Howard zeigt einige überraschende neue Entwicklungen im rasant wachsenden Feld des Deep Learning, einer Technik, die Computern beibringt, Chinesisch zu lernen, Objekte auf Fotos zu erkennen oder bei einer medizinischen Diagnose zu helfen. (Ein Deep-Learning-Tool hat sich nach Stunden von YouTube-Videos das Konzept "Katzen" selbst beigebracht.) Lassen Sie sich mitreißen von einem Gebiet, das das Verhalten der Computer um Sie herum ändern wird ... wahrscheinlich früher, als Sie denken.